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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int64))], 'db_size': 3163, 'db_n_attr': 25, 'imbalanced_ratio': 19.94701986754967}\n" ] } ], "source": [ "datasetName = \"folding_hypothyroid\"\n", "pickle_in = open(f\"{datasetName}.pickle\",\"rb\")\n", "example_dict1 = pickle.load(pickle_in)\n", "\n", "print(example_dict1)" ] }, { "cell_type": "code", "execution_count": 4, "id": "a7f87067", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['folding', 'db_size', 'db_n_attr', 'imbalanced_ratio'])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "example_dict1.keys()" ] }, { "cell_type": "code", "execution_count": 5, "id": "b498f1be", "metadata": {}, "outputs": [], "source": [ "myData = example_dict1[\"folding\"]" ] }, { "cell_type": "code", "execution_count": 6, "id": "45807150", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([[ 6, 1, 1, ..., 79, 0, 52],\n", " [ 15, 2, 0, ..., 0, 0, 52],\n", " [ 15, 1, 0, ..., 220, 0, 52],\n", " ...,\n", " [ 63, 1, 0, ..., 29, 0, 52],\n", " [ 51, 1, 0, ..., 275, 0, 52],\n", " [ 20, 1, 0, ..., 278, 0, 52]], dtype=int64),\n", " array([1, 1, 1, ..., 0, 0, 0], dtype=int64),\n", " array([[ 67, 2, 0, ..., 2, 0, 52],\n", " [ 81, 1, 0, ..., 137, 0, 52],\n", " [ 67, 1, 0, ..., 173, 0, 52],\n", " ...,\n", " [ 72, 2, 0, ..., 7, 0, 52],\n", " [ 69, 1, 0, ..., 43, 0, 52],\n", " [ 49, 1, 1, ..., 50, 0, 52]], dtype=int64),\n", " array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", " 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=int64))" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "myData[0]" ] }, { "cell_type": "code", "execution_count": 7, "id": "96d4bda4", "metadata": {}, "outputs": [], "source": [ "k = myData[0]" ] }, { "cell_type": "code", "execution_count": 8, "id": "8b7b6d98", "metadata": {}, "outputs": [], "source": [ "data_con = np.concatenate((k[0],k[2]),axis = 0)" ] }, { "cell_type": "code", "execution_count": 9, "id": "47e7e6a6", "metadata": {}, "outputs": [], "source": [ "target = np.concatenate((k[1],k[3]),axis = 0)" ] }, { "cell_type": "code", "execution_count": 10, "id": "3c507a82", "metadata": {}, "outputs": [], "source": [ "target = target.astype(float)" ] }, { "cell_type": "code", "execution_count": 11, "id": "4c318912", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3163,)" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "target.shape" ] }, { "cell_type": "code", "execution_count": 12, "id": "12120f0e", "metadata": {}, "outputs": [], "source": [ "data_con = data_con.astype(float)" ] }, { "cell_type": "code", "execution_count": 13, "id": "4363fc6b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3163, 25)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_con.shape" ] }, { "cell_type": "code", "execution_count": 14, "id": "9704b7ef", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1., 1., 1., ..., 0., 0., 0.])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "target" ] }, { "cell_type": "code", "execution_count": 15, "id": "f3d7f752", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 6., 1., 1., ..., 79., 0., 52.],\n", " [ 15., 2., 0., ..., 0., 0., 52.],\n", " [ 15., 1., 0., ..., 220., 0., 52.],\n", " ...,\n", " [ 72., 2., 0., ..., 7., 0., 52.],\n", " [ 69., 1., 0., ..., 43., 0., 52.],\n", " [ 49., 1., 1., ..., 50., 0., 52.]])" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_con" ] }, { "cell_type": "code", "execution_count": 16, "id": "1fc0d7b4", "metadata": {}, "outputs": [], "source": [ "def loadDataset():\n", " labels = target\n", " features = data_con\n", " label_1 = list(np.where(labels == 1)[0])\n", " label_0 = list(np.where(labels == 0)[0])\n", " features_1 = features[label_1]\n", " features_0 = features[label_0]\n", " \n", " data0 = np.array(range(100)).reshape((25,4))\n", " return DataSet(data0=features_0, data1=features_1)" ] }, { "cell_type": "code", "execution_count": 17, "id": "9e59a3a9", "metadata": {}, "outputs": [], "source": [ "data = loadDataset()" ] }, { "cell_type": "code", "execution_count": 18, "id": "5c23dc6c", "metadata": {}, "outputs": [], "source": [ "def getRandGen(initValue, incValue=257, multValue=101, modulus=65537):\n", " value = initValue\n", " while True:\n", " value = ((multValue * value) + incValue) % modulus\n", " yield value\n", " \n", "randGen = getRandGen(2021)\n", "random.seed(2021)" ] }, { "cell_type": "code", "execution_count": 19, "id": "122d6426", "metadata": {}, "outputs": [], "source": [ "def shuffler(data):\n", " data = list(data)\n", " size = len(data)\n", " shuffled = []\n", " while size > 0:\n", " p = next(randGen) % size\n", " size -= 1\n", " shuffled.append(data[p])\n", " data = data[0:p] + data[(p + 1):]\n", " return np.array(shuffled)" ] }, { "cell_type": "code", "execution_count": 20, "id": "c9337308", "metadata": {}, "outputs": [], "source": [ "ganName = \"SimpleGAN\"\n", "gan = SimpleGan(numOfFeatures=k[2].shape[1])" ] }, { "cell_type": "code", "execution_count": 21, "id": "ae160a35", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> Shuffling data\n", "### Start exercise for synthetic point generator\n", "\n", "====== Step 1/5 =======\n", "-> Shuffling data\n", "-> Spliting data to slices\n", "\n", "------ Step 1/5: Slice 1/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 597, 6\n", "LR fn, tp: 20, 11\n", "LR f1 score: 0.458\n", "LR cohens kappa score: 0.439\n", "LR average precision score: 0.540\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 601, 2\n", "GB fn, tp: 8, 23\n", "GB f1 score: 0.821\n", "GB cohens kappa score: 0.813\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 600, 3\n", "KNN fn, tp: 15, 16\n", "KNN f1 score: 0.640\n", "KNN cohens kappa score: 0.626\n", "\n", "\n", "------ Step 1/5: Slice 2/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 592, 11\n", "LR fn, tp: 19, 12\n", "LR f1 score: 0.444\n", "LR cohens kappa score: 0.420\n", "LR average precision score: 0.506\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 595, 8\n", "GB fn, tp: 9, 22\n", "GB f1 score: 0.721\n", "GB cohens kappa score: 0.707\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 596, 7\n", "KNN fn, tp: 15, 16\n", "KNN f1 score: 0.593\n", "KNN cohens kappa score: 0.575\n", "\n", "\n", "------ Step 1/5: Slice 3/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 594, 9\n", "LR fn, tp: 24, 7\n", "LR f1 score: 0.298\n", "LR cohens kappa score: 0.274\n", "LR average precision score: 0.391\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 598, 5\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.820\n", "GB cohens kappa score: 0.811\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 4\n", "KNN fn, tp: 16, 15\n", "KNN f1 score: 0.600\n", "KNN cohens kappa score: 0.585\n", "\n", "\n", "------ Step 1/5: Slice 4/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 594, 9\n", "LR fn, tp: 21, 10\n", "LR f1 score: 0.400\n", "LR cohens kappa score: 0.377\n", "LR average precision score: 0.410\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 601, 2\n", "GB fn, tp: 8, 23\n", "GB f1 score: 0.821\n", "GB cohens kappa score: 0.813\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 601, 2\n", "KNN fn, tp: 16, 15\n", "KNN f1 score: 0.625\n", "KNN cohens kappa score: 0.612\n", "\n", "\n", "------ Step 1/5: Slice 5/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2288 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 595, 5\n", "LR fn, tp: 17, 10\n", "LR f1 score: 0.476\n", "LR cohens kappa score: 0.460\n", "LR average precision score: 0.579\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 597, 3\n", "GB fn, tp: 5, 22\n", "GB f1 score: 0.846\n", "GB cohens kappa score: 0.840\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 597, 3\n", "KNN fn, tp: 16, 11\n", "KNN f1 score: 0.537\n", "KNN cohens kappa score: 0.523\n", "\n", "\n", "====== Step 2/5 =======\n", "-> Shuffling data\n", "-> Spliting data to slices\n", "\n", "------ Step 2/5: Slice 1/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 596, 7\n", "LR fn, tp: 20, 11\n", "LR f1 score: 0.449\n", "LR cohens kappa score: 0.428\n", "LR average precision score: 0.510\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 596, 7\n", "GB fn, tp: 13, 18\n", "GB f1 score: 0.643\n", "GB cohens kappa score: 0.627\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 598, 5\n", "KNN fn, tp: 22, 9\n", "KNN f1 score: 0.400\n", "KNN cohens kappa score: 0.381\n", "\n", "\n", "------ Step 2/5: Slice 2/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 596, 7\n", "LR fn, tp: 23, 8\n", "LR f1 score: 0.348\n", "LR cohens kappa score: 0.326\n", "LR average precision score: 0.510\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 597, 6\n", "GB fn, tp: 8, 23\n", "GB f1 score: 0.767\n", "GB cohens kappa score: 0.755\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 600, 3\n", "KNN fn, tp: 15, 16\n", "KNN f1 score: 0.640\n", "KNN cohens kappa score: 0.626\n", "\n", "\n", "------ Step 2/5: Slice 3/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 597, 6\n", "LR fn, tp: 17, 14\n", "LR f1 score: 0.549\n", "LR cohens kappa score: 0.531\n", "LR average precision score: 0.557\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 600, 3\n", "GB fn, tp: 10, 21\n", "GB f1 score: 0.764\n", "GB cohens kappa score: 0.753\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 601, 2\n", "KNN fn, tp: 16, 15\n", "KNN f1 score: 0.625\n", "KNN cohens kappa score: 0.612\n", "\n", "\n", "------ Step 2/5: Slice 4/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 595, 8\n", "LR fn, tp: 26, 5\n", "LR f1 score: 0.227\n", "LR cohens kappa score: 0.204\n", "LR average precision score: 0.364\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 599, 4\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.833\n", "GB cohens kappa score: 0.825\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 596, 7\n", "KNN fn, tp: 16, 15\n", "KNN f1 score: 0.566\n", "KNN cohens kappa score: 0.548\n", "\n", "\n", "------ Step 2/5: Slice 5/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2288 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 592, 8\n", "LR fn, tp: 17, 10\n", "LR f1 score: 0.444\n", "LR cohens kappa score: 0.425\n", "LR average precision score: 0.556\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 598, 2\n", "GB fn, tp: 4, 23\n", "GB f1 score: 0.885\n", "GB cohens kappa score: 0.880\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 595, 5\n", "KNN fn, tp: 12, 15\n", "KNN f1 score: 0.638\n", "KNN cohens kappa score: 0.625\n", "\n", "\n", "====== Step 3/5 =======\n", "-> Shuffling data\n", "-> Spliting data to slices\n", "\n", "------ Step 3/5: Slice 1/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 598, 5\n", "LR fn, tp: 22, 9\n", "LR f1 score: 0.400\n", "LR cohens kappa score: 0.381\n", "LR average precision score: 0.534\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 603, 0\n", "GB fn, tp: 12, 19\n", "GB f1 score: 0.760\n", "GB cohens kappa score: 0.751\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 602, 1\n", "KNN fn, tp: 19, 12\n", "KNN f1 score: 0.545\n", "KNN cohens kappa score: 0.532\n", "\n", "\n", "------ Step 3/5: Slice 2/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 593, 10\n", "LR fn, tp: 22, 9\n", "LR f1 score: 0.360\n", "LR cohens kappa score: 0.335\n", "LR average precision score: 0.343\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 594, 9\n", "GB fn, tp: 7, 24\n", "GB f1 score: 0.750\n", "GB cohens kappa score: 0.737\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 598, 5\n", "KNN fn, tp: 16, 15\n", "KNN f1 score: 0.588\n", "KNN cohens kappa score: 0.572\n", "\n", "\n", "------ Step 3/5: Slice 3/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 595, 8\n", "LR fn, tp: 16, 15\n", "LR f1 score: 0.556\n", "LR cohens kappa score: 0.536\n", "LR average precision score: 0.658\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 596, 7\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.794\n", "GB cohens kappa score: 0.783\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 596, 7\n", "KNN fn, tp: 15, 16\n", "KNN f1 score: 0.593\n", "KNN cohens kappa score: 0.575\n", "\n", "\n", "------ Step 3/5: Slice 4/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 596, 7\n", "LR fn, tp: 20, 11\n", "LR f1 score: 0.449\n", "LR cohens kappa score: 0.428\n", "LR average precision score: 0.519\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 596, 7\n", "GB fn, tp: 9, 22\n", "GB f1 score: 0.733\n", "GB cohens kappa score: 0.720\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 4\n", "KNN fn, tp: 17, 14\n", "KNN f1 score: 0.571\n", "KNN cohens kappa score: 0.555\n", "\n", "\n", "------ Step 3/5: Slice 5/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2288 synthetic samples\n" ] }, { "data": { "image/png": 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7jJycHL3DEEIIQzBUkl61ahXFxcX0799f71CEEMIQDJOkjx07xpIlS3j66af1DkUIIQwjQO8AABwOB3PnzmXevHlERkY2+TydO4c1Y1RnRUZ2aJHz6kXux7j86V7Av+5Hr3sxRJJ+8cUX6d27N6NHjz6n8+TlFeN0qs0UlSYysgO5uUXNek49yf0Ylz/dC/jX/bT0vdT1A8AQSXrt2rWcPn2ajRs3AlBSUsITTzxBRkYGjz/+uL7BCSGEjgyRpD/55BOv72+44QZuu+02JkyYoFNEQghhDIZ5cCiEEKKmOkfSZWVlDT5RcHDwOQfj8tFHHzXbuYQQoi2rM0lfddVVVFRUNOhEe/fubZaAhBBCnFVnkl6zZg133HEHISEh/OlPf2qtmIQQQlSpM0n37NmT119/nYkTJ3LixAluvPHGVgpLCCEENODBYY8ePXjkkUf43//+1xrxCCGE8NCgFrykpCSSkpJaOhYhhBDVnHMLXkFBAW+//XZzxCKEEKKaJk9m2bp1KytWrGDTpk1UVlby//7f/2vOuIQQQtDIJP3TTz+xcuVKVq1axalTpwgJCWHSpElMnjy5peITQoh2rd4kbbPZ+OSTT1ixYgU7duzAZDIRFxdHTk4O77zzDhdffHFrxCmEEO1SnUn68ccfZ+3atdjtdq6++mrmz5/PddddR8eOHbn00ksJCDDE0h9CCOG36syy7733Hr169eLuu+9m+PDhdOrUqbXiEkIIQT3dHcuXL+eKK67g6aefZujQoaSkpJCamsqpU6daKz4hhGjX6kzScXFxPPnkk2zdupXnn3+ejh078swzzzBy5EicTicbNmyguLi4tWIVQoh2R1FVtVFbmRQWFvLxxx+zZs0adu3aRVBQEL/97W+ZP39+S8XYYLIzS/3kfozLn+4F/Ot+2tTOLOHh4dxyyy3ccsstnDhxgo8++oj09PRzClAIIYRvDZpxeObMGZxOp9ex77//nuDgYO655x7Wrl3bIsEJIUR7V2+Sfv311xk5ciR79uzxOr5gwQKGDx8uU8KFEKIF1Zmk09PTef7555kxYwYXXXSR12svvvgiM2fOZMGCBaxfv75FgxRCiPaqzpr0m2++ydy5c7nttttqvBYWFsYdd9xBZWUlr7/+Otdff32LBSmEEO1VnSPpQ4cOMXLkyDpPMHr0aH788cdmDUoIIYSmziQdHBxMaWlpnSdwOBwEBgY2a1BCCCE0dSbp2NjYenfuXrVqFQMGDGjWoIQQQmjqTNJ33XUX7777Li+++GKNEXVJSQlLlizh7bff5q677mrRIIUQbYNj00bs06bg2LRR71D8Rp0PDgcMGMA///lPHn74YV566SV69+5Nhw4dKCws5PDhw0RERLBo0SKuuOKK1opXCGFgzrRU1OxsnGmpcMsEvcPxC/XOOBw+fDiffvopmzdvZu/evRQWFtKpUydiYmIYOnSo1KOFEG6m5BScaamYklP0DsVv1Jmky8rKePrpp1m/fj1Wq5WEhAQeeughwsLCWis+IUQbYk5IxJyQqHcYfqXOJL148WI2b97M9OnTMZlMvPPOOxQUFPDCCy+0UnhCCNG+1Zmk169fz8KFC7nyyisBbenSyZMnY7fbsVgsrRKgEEK0Z3V2d+Tk5NCnTx/395dddhmqqpKXl9figQkhjEU6N/RRZ5J2OByYzWb394qiYLFYsNvtLR6YEMJYvDo3RKtp0FKlQghhSk5BiYqSzo1WVm8L3sqVKwkJCXF/73A4+Oijj2psSjt58uTmj04IYRjSuaGPOpN0jx49ePfdd72OdenShZUrV3odUxRFkrQQQrSAOpP0Z5991lpxCCHaCPuihagrPkCZOAnL7Dl6h+P3pCYthGgUdcUHUFKifW0kx6aN2CaMwzZhXKO7RNprd4kkaSFEoygTJ0FoqPa1kZxpqXA0G4767hLxTMTVE7qru8SxdHG7StaN3i1cCNG+WWbPgSaWOUzJKTiOHYPCAoiOqfF6jTa/o9nu4651QdT8fPd72sODTBlJCyFajTkhEaVnTwjrAJkZNV73bPNTO4RDZSWEhmFKTsGckIhl2XLM985qV62AkqSFaOdau9brSsREx3hd11XScCVkdm4HRYHyMpxpqe73mRMSUTuE45g7G9sD97VKzHqSJC1EO3euMwkbm+RdI2IyM7yu60xLRc3KwvHYIzg2bdRq3lYrOJ2oWfvdido2eiRs+QycTvhiS5NibkskSQvRzlWfSdjYpOuZ5Bvz2erXNSWngOoERcGZlopl9hyU6MsgKBhUFaJjcDz2CJzOOXuSa0fUe8223hUiSVqIds5d6616CNfYkbVnsm3MZ6tf15yQiPmJ+Sj9L/JK3Er//pifmK/VsBUTWCwQFIRy2+1YX1hSNQLfj+PPD/ls7Wvra44Yprvjq6++4rnnnuPIkSN07tyZadOmccstt+gdlhDtTmN3V6k+Xfxcdmbx/EFR17k9j5mSU7QRtr3S3dpnTkh017iJjkGpel9bZIgkffLkSWbOnMmCBQtISEggMzOT6dOnc/755zNs2DC9wxOiXTmXNToa89kaDwqr/Df9S9J7jiYp/UuGeRyv7dyuY46li4Gzydg1glZAq4G3UYYodxw/fpykpCQSExMxmUzExMQQFxfHrl279A5NCNFCHEsXo+7ehePPD3l1eKRHXMLJDpGsjU50H/Oc4OKrvmxOSMS6cg3WlWvcSbu2LpK2xhBJOjY2lr/97W/u78+cOcPOnTsZMGCAjlEJ0T611IM2n+d1OsFe6dXhkZT1BT1sRdwwYoD7mKum3JSad/UukrbGEEnaU1FREffccw8DBw4kISFB73CEaHcamgjtixZiGxqHfdFCoP7kXv285ntnQZ++0KuXVlfetBE1P5/4kp+YH9eRq/p2BrwfTHr+3nV92wP31Xndtr4OtqKqqqp3EC6HDx9mxowZ9OvXj4ULFxIYGKh3SEK0O2Xr1lH82uuETb+d4DFjan3fiYsHoBYXo4SF0WPfD+SMvI7Kw0cI6N2bbps31Xpey+DLse/ajWXwIOy7dhM2fRrBY8bU+Lz2/mXu12u7PoqCqUsXAvr0IXLFh7Vct/bzGJ1hkvSOHTuYMWMGt9xyCw8++CCKojT6HHl5xTidzXs7kZEdyM0tatZz6knux7ja2r1UX7LUNmGcttbGhVFYV67xuh/PTgv1vXe0TgxLAHQIh/BwlE6dUA8c0Nb06NoN64bN2KdN0R78RUX5fPDnuj6xcShFhTUeQLrfV895GqKl/24iIzvU+pohujuOHj3KXXfdxezZs0lJaZv/JBGiPXFs2giZGZifmH+2z/neWbW23zmWLtYS+PeZYLdrtejzIlEuuMC9YBK2CggIgLAwoP5WwIYu9NTYlkKjMcRI+u9//ztvvvmm1zZdAMnJycydO7fB55GRdP3kfoyrLd1LQ0annvdjmzAOjhwBkwIRnSEsDPO9s9z9zI6li6G42H0cfPdE60XPkbQhknRzkSRdP7kf42or9+JOqlSNnjP2+NypJWznVn55egEAyrDhWmmi0gEBZq8ROFCjVNIcJYrmpGeSNlx3hxDC2JxpqVBYiNKpk7YinY+dWhybNpI/+49w5LCWfKtKI6BCaak7yfvi6vIgPLzOEkVbX5OjoSRJC9EONSXBuT5DdIxXS5trpxZi47SdVK69CsecB1DLy7V1Ni6MOlu26HG+drKj2e51NtwxXBiFMmw4jkfmaaURqLPU0dbX5GgoSdJCtEMNTXCeydy1kJG64gOvWrFl9hxtlPy//8Khg1qHhqpqDwjPv8BdY7ZPm4IybDiEhIBTda+z4TkyJzMDbDZwOuD4T9gXLaz1h4ln/7M/j6qlJl2PtlInbCi5H+NqzXupbd2M6jxrw+6FjBQTREaidOrk/rx92hTU3bu15GoygdWKKaITTlslhIdry4s6HGA2o0ychPrl5wA1HhICOBY8DbmnwWzWukBCQ1H6X1Rnbbqla9jtvgVPCNG6PBcrqithe7aveS1kdOwo6pHDOPLzAbQacmSkllCHDYfMDILjYyndtlN7rbISysshwIK64oOq+vTZ5GxZtlwrfTzz96r1ohUtqQcFgarWW5tuSA27rZJyhxDtXF2lD19rPiudOoHDqY1y8XiQeMEFWFeuca+VUfHpZ4DW2UFAAAQHayPtqkX9q1/XmZYKOaeqrqxqW2d171GjE8RX/J4PMv2NJGkh2rnGrm1hSk6BXr2gT1+tXBEdA+Vl7t2/XedzFBWh7vkW9cvPtcX8B1yKkjIVpf9F2szD/Hwwm1Hz87VacnSM9qDRxam6E29dNee2vjZHfaTcIUQ719j1o30txI+ioK74AEfMQPfrzkk3UJmb6/6M+73RMVq7nqJoDxgdjrOj+I7nQVGh9tDRaq2xNrRj6eJznuRSfTq70clIWghxTrS9CVVQTO5k69lW53o46Fi6WBtZv/eO9vDRZoPQMHct2TUiVm6ZjDJoMOb5C2quDV1SgrrnW68+68a24vnq6zYyGUkLIc5J9VGyfdoU1Px8TMVFKD0vdJcrOHFcq2N37qL1VZ84DqWlUF6OY+5suHYE1qrODNfDTGfGHsjMcD9ctE0YB3k/e12/sWtzKBMnuUfSbYEkaSHEOXOVOFytcISHE9CnD47f3QpUJXCLFQICMD/0sDb6zT2t7Q5eUKid5PPN7vO5Rsfs3wdBwe59C7kwSpvFeGFUjWs3VEMXZjIKKXcIIZqNqyxhvncWkSs+9C5XVO36bU5IrPr+Iq0VL7yj9uEO4V7nITwcQkK9Hy7u3K6VVnZub1RcbXmyi4ykhRBNVr3Huq7NYj2P17fDuDkhURtNFxZqnSOuh4uxcfDFFu1rI3jWrdtam56MpIUQTVbXQ7uydesaNHp170UIXu93P0icOMndYqcUFUJEZ+0rDR8ht+U2PRlJCyGarK6HdsWvLatz9Fp9FF59tFvbqNzzeg1tzWts3dpIZCQthGiy6jMSPYVNn1bn6NW1YJPjsUdwbNpY72jX1/R1d2se+O2KeDKSFkK0iOAxYyiOHVrr62qHcCgqAosFZ1qqz2TvmZirl1Y8Nx6AmnXt6hq6qJTRyEhaCKEPV4eGw1H3aLsqMXuOtJ1pqdpmAkfPlkdqG9H7OldbIiNpIYQuPCeV1JZcq6/C5/k+1wp8jVlzpC1uSCvrSdfDn9YrBrkfI/OnewH/uh/Z41AIYVhteSKIP5AkLYSoU2NqufZFC7ENjcO+aGErRNY+SJIWQtSpMRNB1BUfQHExauqblK1b1wrR+T9J0kKIOjWkc8K9k3hsnLbHYWAgxa+93opR+i9J0kKIc+YqiShFhZifXYQy4FIsgy/3qmVLbbtpJEkLIc6ZZ0nENfK279pdYw/DttinrDdJ0kKIc+arJOKaFu7aCIDomBq1bRld10+StBCiyb4+mMfDKzP5+mBejdeCx4zRVrer2j2czIwaibzGVG9J2jVIkhZCNNnqPSc5fqaM1XtO1vqeurpDqr8mJZGaZFq4EKLJxg/szuo9Jxk/sHut76lrmdDqr7XVqdstSZK0EKLJrurbmav6dm6287XldZ9bipQ7hBDNQurJLUOStBCiWbREPVkSvyRpIUQzaYl9BOVBoiRpIUQzqWv6eFNHxG15A9nmIg8OhRAtrvomsw0lDxJlJC2EaAXVR8R1TYIR3mQkLYRocdVHxJ6TYJqzhc8fyUhaCNEiytatq7UOPX5gd84/L7jOSTBCIyNpIUSz+vpgnjYL8etPGVJLHbq5J8H4MxlJC9HONXd92FXKWBud6LUKXm2dHZ6dHw3tAmlP/dOSpIVo56ovktTYBPjmV0f4/SvbePOrI4BWyuihljPm61Wo+fmoX37us9fZsWkjttEjccx5APWH73GmpTa4L7o99U+363LHtK9ucf9+2TXv6RiJEPqpvkhSY9vl1n2fQ5nNwbrvc0gpP8CQpYsZcuI42O2gKHBhlM9eZ2daKpzO0b6pqPBaCa++vuj2tBCTYUbS+/bt4/e//z2XX34548aNIyMjQ++QhGgXrurbmb9PiHbXiBsygcRzV/Axl3Yj2GpmzKXdtMR7NBtsNrBatQQ9bLjPc5iSU6BrNwgKgmtHuEfF9e2nCA3bd9FfGCJJ22w2ZsyYwZgxY9ixYwd3330306ZNo7i4WO/QhGh3GpIA1ffTtF3B01KZ/PqjpPUtZOo1vSA6BgICoEskEf/3T6wr17gX/a9emjAnJGLdsBnr/3ahFBXWWhJpL7Xn2hgiSW/fvh273c7UqVOxWCyMHTuWfv368fHHH7fodZdd8577lxDiLF/J0XP0THhH7aCqeifXzAwI64DSsyfBY8bg2LQRNT8fwsMxJad4PaR0bNrIl7Mf5U/LvmR70tRaSyJNqT37U3I3RJL+8ccf6du3r9exPn36kJWVpVNEQrQ/nonNV3JUV3wAJSWoKz7APO/PKENiYei1UF6mjaDxvdMKJ0/AkcM4M/bw0ZYfOJ59ko+2/IAzLZX0jv05UVhOutrVa/TuisXXvojVY/XFnx4sGuLBYWlpKUFBQV7HgoODKSsra9R5OncOa86w3CIjO7TIefUi92Ncet5L7odpqMeOYv7wXTrecyfFr71O2PTbYedWil9bhrlfXxwZ32EdejVhHYMptphxnjhGpdOJmvomllArYYMHU1hUgPryEs4c3IupqABHeTmoKqz8kBuuLOaj0H7ccOIgne65kxvf38Ta3r25dVhvr3t3xRJgCSBy9ao6Y428ZUKN18s84g9upj9Tvf5uDJGkQ0JCqKio8DpWVlZGSEhIo86Tl1eM06k2Z2hERnYgN7eoWc+pJ7kf49L7Xhy/S0ZNS8Xxu1spjh0KsUMpBuzTpmgbyZaXQURn7Lm/sO6dDaT/KoEk5y7iD/zItgsvJ/1YR5L2biD+0GEASlPfQQVQFO31oTczvl9Hnkx/E7VDOL888CCxEycRd0Epjrtu4XheHpSXodwyGZNHLL7+TBz1vI5H/MXN8Gfa0n83df0AMESS7tu3L2+++abXsUOHDnHjjTfqEo8Q7YWrtGFKTql1xTlXuxvRMZCZgSk5hfTvKzlZAWujE4nf9zVpQ27kZMduFHXtAdlHSL9kJEmHvyb+0E5AIf2yRE4GhJGuduWaZcuxDY3TSifvLMeR6tRG2qo2wFLfT2P7+D+wemx3xvfqzlU+4m5Pq+MZoiYdHx+Pqqq8+eab2O121q5dy/79+0lMbB9/CULopSG1W1e3h2X2HCzLluPM2EPSZ+/QvfA0YzM3gq0CUEEBtaSE9EtGcjK8G+m9rwJrINv6DKYwpCNhIUGMH9hdqyOHhEJgoNZH7axK0kpVOgoMrHMXcsemjdiuvw5b/CDtIaafM0SStlqtvPrqq6xfv564uDj+9a9/sXTpUiIiIvQOTQi/5nrQV9/UbU/qig+IP7KLJ9c+S/zPB8BiJfn79VxUkUfy1x+SlPkp3Qtz6J9zkL8Ov5u0wTdQEhhC+C85xB3Zpf1AcDpRLo1GSU6BsDCU226HyEjtAoFBNRZg8uwscaalQs4pqKjQHmb6OUVV1eYt4upIatL1k/sxLj3vxVV3VqKisCxbXuN1z7KIM2MP6ooPUCZOwhQz0H3c8dgj4DG34a/j5nGyYzdCK8sJt5eR9P0m4n/KQJk4yV02MSckamt2LHiabcE9SI8eRVLudwx75Xmv67vKI4SGYn5iPo5n/g5n8tl26318fGE84wd2b9EFm/SsSRtiJC2E0Fd9sww9yyKW2XPY8cd/8JfyXvyv0Hy2Zh3VSytfACgKSRkb6F54muRDX/Dk7jTij+zSShpVCfq/6V/yp2Vf8t/0L+F0DunRozjZsRtr42/SShoTxmGbMA7Hpo1aYg8NRZk4SZsEs/4zrNt2s7ZDf3dLn78yxINDIYS+6n0QFx0D+/e5+6FX7/uFkwFhrNn3C3E/rj7b/dG5CxScAbud+OzdYDaRfukoskwdyBowkaR9W7gyOlrrke45mpOF5aztfRXxX/6HpL2bWTviVsZF2HE8Mg/KywG0UXNoKHTthilmoFdYYzM3kt6xP2OPZgHDWuhPR1+SpIUQNdgXLdSmfod3RBkzVqv9Koo2oxAYf3EEqzNzGHtgK+qpYxAeDtGXwddfaQsrVUm/5DpOhkVy5LzzCXTYSL94BPGfLIcz+SSVBpH+66GM3bMeKiuJP/4dVzpiUJ/7ACoq2BY1SCt/ZH5K/KFvwaRoJRVw/0C5OmkYV/r5QkuSpIVoxxybNuJYuhgA872zgKrSxveZ2ki2vBw1LVVLvGYzan4+9kULicvM4Ir8fLZxHvcPmwGBQSSf3EG853yH4GD6nz7EkYieRB/fS3FIB5KO7oC8n7WkvO8r4vduZVvUIP46dq6WjF0/DAIDSYufyMnQLhQOCdVG5SpQYfNK1O2hFU+StBDtmHvVOtfvATVrP1RWgsUCnSLgF20zgG0XxJB+ySiSvtpC/JlsCA/ntauS+SUoHBRI7zEIog6eHf3+lEFW1z4EVtooDg7jyY8XogwajBrRWVuiNCgI7HatFh3ejfTLErmy8yDULz8HoCyiKw67QllgCHTsCEVFUGmHoMBG7zrelsmDQyHagdrWulDLy6sSshVTcopWNlBVCA5BiRmIdcNmlMlTwGQ6m0yjR6NERWG+dxbFweEAKKpK0rb/uN+TNuQG/vqbB+mfc5DuhTkkZX6qLcbUIZxtvQbx1xv/TOplv+Wv18+mf+5hutsKGD/kQq3mfDoHThxHPXMGFFC6doPAIK2fukM4Sv+LGtUy2NbJSFqIdqDWhfz3VnVFlJednXn4xHyvBfUts+fgiBlI/3V7OGKNon9QAP8r6EXaD2ApL4KAQC4/lkn6gFH0P7EfgMLAME6GdwNF4clPngeHQ0v+Wz4jfexcTgZHcOSi4QRW2igMDCW8vATnju04Nr4LdjvbogZRHBiKyekkOPeUFmNAgDb6BtR1a+GXPBz5+X4/opYkLUQ74GsnE8emjRDWAYoKoUM4atZ+rauix/mY752FM2MPjsceQZk4CcvsOfxY0B3l52I2lHZlZ6SFk85AsEL3glNknn8JCioEBvLk+kVs69RHK3vs/Uy7WNV0jG1RgygMDCWsooThB/5LVre+7oSeXgjxVQ8d06NHYXFWEuB0cOuuj7QJLz17ov70E+ru3eB0gMnc6n+OepAkLUQ74OsBmzMtVUuegYFQVnq2K+PIERx/muP+Xl3xAcyeQ5JymsWlCorZhGKx0qMkjxLFzOkOkYBKgNNJ0vaPoLiI+MLd2sM+D9uiBrHk2j+gqE46lZ4hq1tfrQwCvDvkRgoDQ9kWNYj47N0kZX6qJfmsL4g/+T3mJ+ZjTkjENmGcNtsQICTY/bDTn0lNWoh2ypScovU2l5d7tc3hdHh/H9UL24RxXDH/Ae7b8jpRZ04wuV8IL6x/hl8V52Fx2AlwOrnvize0xOx0+rxeevQoFFTsZgunOnZjb9d+LLvqFtKjR6ECJYFhpEePAiD+6Lc81SUPLujJo394ju29BgNVHSh9+kKfvu7EDf61yH91MpIWoh1yt955JmNwt7+5JpIAcPBHsNnB6SD+yDfEl/6EcqQnakHB2RFv5qc1Rs5ezGb6W+0cURQ6VBSTH3IeqmKiKDCMcksQdlMAHSqKvUbTavYR0ruN4KRNYfWek1zVt7PPfxE4Nm3U2vIUxS+7PiRJC+HnPNfdAHA88SgUFvh+s6p6J2gAm53UwTew4ZIRjN67hZRvV6NW9UPHZ9csa1TnmpRyytqZ0oBASgOCCKqswKmYuPxYJpnnX4LFYafMEoxTMZMePUo755bPSOpTQHrMb/ht1gYcHbUV8TyXVnV9j2IC1emXk1okSQvh5xwLnobTOTiOHYOwsJoJ2mKpMaL2mu2XvZsNl4ygzBLEhktGkPLNKm3qtw/VP5caO4HVMddjcdhRUdzLkVYEBGJSnZw4rxv3ffEG6dGj6J9z0KtODRB/6Bvij+yGiM44C48A1OhS8Xwo6m+jaJAkLYRfco2eiY6B3NPawdM5WidHddVLHuDRE62Nakfv3aKNpPd9riXiSxN8ljiqf27DJSNwomA3WxifsZ5PLxpKSWAYgfZy7AFWFBSv0bgryYNWl9bWmVbAZNJmQV55dY2FoPx91qEkaSH8iH3RQtT33tEmqKgqZH6nTQQpr9ovtIH7hrprzd9vgoAAUnauJGXnyrMdGqhnyxIe+ucc5EhET34J6sDvbn+ZrgU5EHIe0cf3ktWtr7YBi6JgdlTS55dj7lGzKzkXBoa6HyDGH/9Ou4/OXbTRf3k5bP0CBl7enH9khidJWgg/oq7QFidyCwoGRyVcGq1NXKml86K6+OzdxOfu1/qoIzq713ouDAxFUZ2oismrLOGS1a0vCiqnztMW6z/V8VcMyDnAifN+RUlgKCVB2mbRZYHe+5e6RuBh9lK6F50maf8WGHotSlGhtlb1gqe1JK0ovifl+DFpwRPCjygTJ2ndGR3P01rVOnfWygXZR1BSprKtXxx/HTuXbVGD6jmRAuUVbAvuwV+vmKLtYRjeDcVkIir/OPd98QZAjXMlZX6q1Z61LWgxqU5t5iEq3Qtz6FBRAqiYVPXs9PHxD9P/9CG6F+Yw5Mi32r8AnE7YuR2iY3CmpaKMGYsyJBalnnWv/ZEkaSHaKF+9wZbZc7Bu24318/+iDBsOJ45rO5qUlqF++Tnp8Te4a8Y1uBbsh6pE6XCPcEGle8nP3Hr4C23brOzdpA25kf1d+/LukBvdH3PVr62VdjqX/EJs9h4qAqzEHs3gybXPcs/W5Qw4dYCkzI10L8wBFE6GdSHrV/14cu2zZHXrq8V3yXVQ6UB9ZznqNztR163Fsmy5ez1pZ8Yev+2Lrk7KHUK0Ub7W4/B8YKguf8M9HRsUOHSQJMe/z07X7nje2S4NRfF471mefdCglSWIyiM+ezellkAcJjMllkCvz2R160uorYxuRT9THBxGYKWNrG59gZote+5ukJ92QmAgSXs3k37JSG1/xIT7zj6crOpIcd0z32dCZaWs3SGEMLBqu6WARxLbv+9s0jWZtN+r1ZJk127aa4qiLUPqY1KK5/v/OnauV+dGiL2CAqeDULtWA3cl3P45BwG8Ertn/bp6m577emYz8XkHiF+70/taR79F+X0yANuTprJ63y8k7d1M/A9fNv+fqQFJkhaircrMgKBg1C8/x56ZoY2e8/PBbIaQUO1XYYHWBx0cov1eUaC8nG394kiPGU3SL3uJz95NevT1nAyL9OrYqJ5Mq4+qY4/uYcMlIxhydA+AR2kEnlz7rDvM+tr03BwOKNRaBL2u1bsPltlztM+qXTnZrQNru97ClZaidlGblpq0EG2Ua/NYiotR93yrtd4VFkJJsbZgUmkJyu+TUfpfhHnen7H+bxfWr7/BvPAF0geP5WSXnqyN1koFSae+pUcQJGV94T5/esxoTv6qN+mDfgtoydZVjwatrOFZykjK/JTuhTlaqaKOh5Ou9/nqDnGN/t3XyjuA+d5Z7vp7knKa888L5oYRA7AsW+5V6vDX9TsUVfVRiGqj8vKKcTqb93Zaeiv31ib3Y1xNvRfbhHHa7iqdu6BccIE2on7vHbDZtFH1hdoC/Z4J7euDeXy05QfGbniT+OxvtTa9ysqqpoyqZUV7DSZ9yFiScvYQv3V1jetWH2m7uEoV3QtzvEbUjdbxPMyPPnF29buj2XBhFNaVa3y+3T5tCmp2NkpUFJZly5t+XR9a+r+zyMgOtb4m5Q4h2jjzvbO8pkU7Nm3E8X6aNiqtrIQjh3EsXez1nrgjuxjyxiNaicFW4bN/Ov7ILuKP7Kr1urWt21G9LNJoigJmM0q/fo16KOhrzWx/IElaiDau+rRo116FbhYLcHbNCwDHvD+e3cfw/PPh2DHfJzeZ2dbT+6FiauyEs4st7VxZ4yOuxO2e3l3PAkxeQkKgtBRCw84uCOUqX1T9i6A2/jo9XGrSQrRhvuqwpuQUbaup4GAIC8P89DOY752l1a+jY7TdVyorz56kWoJ27d69LWqQ1is98HpOdjzbW+1abOnjSxNqrT17PhxslNJS7WtJMc601LMthYWFKJ06+WUSro8kaSHaCF8J2ZmWipqVheOxR9zHzQmJmJ+YjzLgUvfC+OaERK1Wnfqm97TxehZXAkjas57uBWcf9I3eu4Vgezlh5cVkdzqfJdf+oUaiTsr6ovaHg9VVtQGCx2Qaj+nfpnY4y9CTlDuEaCN8TV4xJaf4XPDenJDo3qPQseYj7aHb4UNnV5ULDPRO1h6q15Sr15775x4mq1tf+uccZMMlI3wuthR/YBvxB7b5vpHqE2dCQiA2TouxuFhbTvXCKPe0cH8tYzSUJGkhDM5zFqECXrVaZ1oqysRJqF9+jpqfj+2B+7TkFhsHX2zRHghuqdoMVlG0Xx3CtVLI6Ryfswx9LR3q2cHh2Q/tWgu6UQ8Jw8KgyKNTIigYjmajdOqEqarmrP3gMWm94O2ctODVw59avEDux8hqu5faWss8j4P2YJBf8s6Ols1m73KG2awd96xH1+OvY+fyY+cLqQywMj5jvXu50gZtmeWpavTs/mzWF9pIW1EgsquWuHNzQXVqMyFzT4OqagtGZWbovqC/ni14UpMWwuBqq8m6J7O4ZhqGh8O1I8Bq1UbL1cdfDkejEjRopY/KACtORWHDJSOAmpNa6uSqNVfF4q53979We11VobRE69pQne5FnpT+F2F+Yj5kZnh1pbRHUu4QwuBqq8m6F1WqqkkT2RWlqBD1/Au0mYcBAVq5o541pOsaGcdn72Z8xnp3y12jVftBUaOHOigIZeIkr/0KvfYvzNhTY32S9kaStBBtmDMtFSpsYLeByYxaWKiNqMPDtWPVN5X1oda1NKq4dmVpDvHZu4k/tkfr6OjT12v2oM8fRlXrk7Tn2rSUO4Row0zJKdqUbtCWHS0uQhk2HKVTJ20dac81omtR51oazc1kgi6RKAMvr3Niivvt7bz9DiRJC9Fm2BctxDY0Dvuihe5j5oRElJSpWvIDreZc9aCNC6O0+rSpjv/Ng4OJP/5dw2vM5yI4BEJCUMaMdT8ArW9BJHNCYo2FlNobSdJCtBHqig+gpET76sEUMxC6RGpTvCM6u2u61pVrMD/9jHtauE99+jb6YWKTlZVCeTnqurVacl662OdDQX9dza6pJEkL0UYoEydBaKj21YMzLdXdeqf07AmcHaGaExLhvE61n/T7TJ+HvaaGNxezWftaWKC1C4LPUobnpB0hDw6FaDMss+dA1eL3nkzJKTjy892/r5Hk8n5u9LVqe5jYpB5p0DpNqnb/Jjqmzt5nf13NrqkkSQvRxvnqinAlOWdaas0WvFr2M/RU23Kj9XWCuAUHa2UUu/1s73NRYYPWeW7v08Crk3KHEH5Izc/HsXSxNmrt1Ru6/UobzbpmInp+74NrwkpWZG9SUhaTGjsBaEQnSIdwAnr3gg4dtHVCLvQua0jdueEkSQvhZ5xpqdpiRUezITNDe4D40MNVSdmk7W6y/jPMC56D0NA6z+ValrTRsw1/zqXy6DGI7Ip5/gIthmprXkvduWEkSQvhZ9ztdx6jVy0ZKoCKMmw4cHZJ07q4liWtMdvQ1wjc9WDQYgGLBSUw0Oca0I5NG93T2KXuXD/D1KTfeustli9fzpkzZ+jduzd/+tOfiI2N1TssIdocXzVd95KmllCv2XvmhESct92Ompaq1Y/NZm2Njyq1zjb0VdPuEqltglu17Kg5wIzqIwm7F/GPipLacwMYYiS9YcMGXnvtNV5++WV27NjBrbfeyl133cUvv/yid2hCGF5D6rvujQD6X1Rj9GqZPQfzPxZqK9GFhGq9002hqtoU7p3bobAQU0RErd0b7X0WYWMYIknn5uZy9913069fP0wmExMnTsRsNrN//369QxPC8Bpa361r9p4zLbWq68OpbbV12+3aTEWLpe4Ziy6uDo6oKG0kXV6GZfDlXm9x/TAB2v0swsZotXKHzWajoKCgxnFFUZg8ebLXsR07dlBaWsqvf/3r1gpPiDarOfqKPc/hKpc4YgZqHSLFxdpCTbYKuPJq2PpF1SxFBcJCITRM68UOC8OybLm2znVQMPZd33pdw9fOMqJ+rZakd+/ezZQpU2ocN5vN/PDDD+7vs7KymD17Nvfffz9dunRprfCEaLOao6/YnZirRruuZO1MS9VW1rNVaIl57w9al0ilA4IC3Q8ePX9IuBJ+2PTbKfa4hkxSaRpD7cyyefNmHnroIe644w7uvPNOvcMRot3JnXgzlYcOE9CnD5ErPqRs3TqKX3sde3Y26s8/aw8WrVYUVaXToucIHjNG75D9nmGS9FtvvcULL7zAP/7xD66//vomnUO2z6qf3I9xGeFeXPsmVp+y7bnPYkO3szLC/TQXPbfPMkQL3scff8yiRYt46623GDhwoN7hCNFu1bULjNSR9WGIJP3qq69is9mYOnWq1/Hnn3+ekSNH6hOUEEIYgCGS9KpVq/QOQQghDMkQfdJCCCF8kyQthBAGJklaCCEMTJK0EEIYmCRpIYQwMEnSQghhYJKkhRDCwCRJCyGEgRliMktzMZl8b6pp1PPqRe7HuPzpXsC/7kevezHMAktCCCFqknKHEEIYmCRpIYQwMEnSQghhYJKkhRDCwCRJCyGEgUmSFkIIA5MkLYQQBiZJWgghDEyStBBCGJgk6Ubas2cPl156KT/99JPeoTTZW2+9RUJCAkOGDOHmm29m586deofUKPv27eP3v/89l19+OePGjSMjI0PvkM7JV199xYQJExg8eDCJiYm89957eod0zgoLCxkxYgQrV67UO5Rzcvr0aWbMmMGQIUO4+uqreeGFF1o/CFU0WHFxsTp69Gi1f//+6rFjx/QOp0nWr1+vDh06VD1w4IDqcDjUf//73+rgwYPVvLw8vUNrkIqKCnXkyJHqG2+8odpsNjU9PV2NjY1Vi4qK9A6tSU6cOKEOGjRI3bBhg+pwONQ9e/aoV1xxhfrFF1/oHdo5eeCBB9SLL75YXbFihd6hnJOJEyeqjz76qFpeXq4ePXpUHT58uLp69epWjUFG0o3w1FNPMXr0aL3DOCe5ubncfffd9OvXD5PJxMSJEzGbzezfv1/v0Bpk+/bt2O12pk6disViYezYsfTr14+PP/5Y79Ca5Pjx4yQlJZGYmIjJZCImJoa4uDh27dqld2hNtmrVKoqLi+nfv7/eoZyTPXv2cOzYMf7yl78QGBhIz549SU1NJT4+vlXj8KtV8M6FzWajoKCgxnFFUejSpQuffPIJR48eZd68ebzyyis6RNhwdd3L5MmTvY7t2LGD0tJSfv3rX7dWeOfkxx9/pG/fvl7H+vTpQ1ZWlk4RnZvY2FhiY2Pd3585c4adO3dyww036BhV0x07dowlS5bw3nvvMX36dL3DOSeZmZn079+fJUuWsHLlSgIDA0lOTub2229v1TgkSVfZvXs3U6ZMqXHcbDazefNmnnnmGZYvX47JZPx/fNR1Lz/88IP7+6ysLGbPns39999Ply5dWjPEJistLSUoKMjrWHBwMGVlZTpF1HyKioq45557GDhwIAkJCXqH02gOh4O5c+cyb948IiMj9Q7nnBUUFPDNN98QFxfHpk2bOHToENOnTycyMpJx48a1WhySpKvEx8f7/Ce/qqpMnTqVWbNmccEFF1BYWKhDdI1T27142rx5Mw899BB33HEHd9xxRytFdu5CQkKoqKjwOlZWVkZISIhOETWPw4cPM2PGDPr168fChQvbxGCguhdffJHevXu3+ZKgi9VqJSwsjJkzZwJw8cUXc/PNN7Nx48ZWTdJt77+EVnby5El27drFU089RWxsLCNHjgRg/PjxrFmzRufomuatt97iwQcf5KmnnuLOO+/UO5xG6du3L4cPH/Y6dujQIfr166dTROdux44dTJo0iVGjRrF48WICAwP1DqlJ1q5dy/r1690lnKysLJ544gkef/xxvUNrkj59+lBWVobNZnMfczgcrR9Iqz6m9AMFBQVturtj7dq16sCBA9Vvv/1W71CapKKiQr322mu9ujsGDRrUZrpTqsvOzlYHDRqkLl++XO9Qmt348ePbdHdHeXm5eu2116p/+9vf1IqKCnXfvn3qlVdeqX7yySetGoeMpNuZV199FZvNxtSpUxk0aJD71+bNm/UOrUGsViuvvvoq69evJy4ujn/9618sXbqUiIgIvUNrknfeeYeSkhKef/55r7+PZ599Vu/Q2r3AwEDefvttjh07xrBhw5g+fTrTp0/n+uuvb9U4ZPssIYQwMBlJCyGEgUmSFkIIA5MkLYQQBiZJWgghDEyStBBCGJgkaSGEMDBJ0sKvXXfddVx00UXuXwMGDGDkyJEsWLCA0tJS9/t++OEHZs2axdVXX82gQYOYOHFirTNKt2/fzkUXXcSjjz7q8/WDBw+SkpLC5Zdfzm9+8xs2bNjQIvcm2gdJ0sLvPfjgg2zdupWtW7eyefNmnn76aVavXs38+fMB+Pzzz7n11lvp3r07r732GqtWrWLcuHE8/PDDLFu2rMb5Vq9eTa9evVi7di3l5eVer1VUVDB9+nR69+7NihUrmDRpEg8++CB79+5tlXsVfqhV5zcK0cpGjhyppqam1jj+r3/9Sx0yZIhaXFysXnnller//d//1XjPyy+/rMbExHhNOa+oqFBjY2PVlStXqpdddpm6atUqr8+sWrVKvfrqq1W73e4+dt9996kPP/xw892UaFdkJC3aJbPZjNVqZfPmzRQVFTF16tQa70lOTub1118nPDzcfWzz5s0UFxczfPhwrrnmGlasWOH1mV27dnH55ZcTEHB2gckrrriCb775psXuRfg3SdKiXXE6nWRkZPD2228zatQo9u7dS+/evQkLC6vx3rCwMIYMGeKVcFevXs3gwYOJiIggMTGRHTt2cOzYMffrp0+fplu3bl7niYyMJCcnp+VuSvg1SdLC7/3jH/9wL1x02WWXkZycTExMDHPmzKGwsNBngvaloKCAzz//nMTEREB7KGk2m71G02VlZVitVq/PWa1Wr+UuhWgMWfRf+L277rqL8ePHA2CxWOjSpYs7kXbq1KnBGzmsW7cOu93uXtT+vPPOIy4ujlWrVjFr1ixMJhNBQUE1ErLNZquxm4wQDSUjaeH3OnXqRFRUFFFRUfTo0cNrpBsTE8Phw4cpLi6u8bmioiJSUlL47rvvAK3UATBq1CgGDBjAgAED+Prrrzl16hRbt24FoFu3buTm5nqdJzc3t0YJRIiGkiQt2rWhQ4cSERHBG2+8UeO19957j927d3P++edz/Phxdu3axcyZM/nPf/7j/rVy5UpCQ0PdJY/Bgweze/duKisr3efZsWMHgwYNarV7Ev5Fyh2iXQsKCuLxxx/ngQceoKSkhJtuuomAgAA2bNjA0qVLmTt3LhEREbz00ksEBgYyZcoUr24PgJtuuon333+f/Px8Ro8ezfPPP89f/vIXpk+fzpdffsmWLVv48MMPdbpD0dbJSFq0e6NGjWLZsmUcOHCA2267jZtvvpnPPvuMZ555httuuw2ANWvW8Nvf/rZGggaYPHkylZWVrFmzhpCQEF555RWOHDnCTTfdxAcffMALL7zAxRdf3Nq3JfyE7MwihBAGJiNpIYQwMEnSQghhYJKkhRDCwCRJCyGEgUmSFkIIA5MkLYQQBiZJWgghDEyStBBCGJgkaSGEMLD/D46Y78sXlVXIAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 595, 5\n", "LR fn, tp: 21, 6\n", "LR f1 score: 0.316\n", "LR cohens kappa score: 0.298\n", "LR average precision score: 0.389\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 597, 3\n", "GB fn, tp: 8, 19\n", "GB f1 score: 0.776\n", "GB cohens kappa score: 0.766\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 1\n", "KNN fn, tp: 14, 13\n", "KNN f1 score: 0.634\n", "KNN cohens kappa score: 0.623\n", "\n", "\n", "====== Step 4/5 =======\n", "-> Shuffling data\n", "-> Spliting data to slices\n", "\n", "------ Step 4/5: Slice 1/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 593, 10\n", "LR fn, tp: 22, 9\n", "LR f1 score: 0.360\n", "LR cohens kappa score: 0.335\n", "LR average precision score: 0.433\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 598, 5\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.820\n", "GB cohens kappa score: 0.811\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 600, 3\n", "KNN fn, tp: 21, 10\n", "KNN f1 score: 0.455\n", "KNN cohens kappa score: 0.438\n", "\n", "\n", "------ Step 4/5: Slice 2/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 593, 10\n", "LR fn, tp: 21, 10\n", "LR f1 score: 0.392\n", "LR cohens kappa score: 0.368\n", "LR average precision score: 0.496\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 599, 4\n", "GB fn, tp: 9, 22\n", "GB f1 score: 0.772\n", "GB cohens kappa score: 0.761\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 4\n", "KNN fn, tp: 18, 13\n", "KNN f1 score: 0.542\n", "KNN cohens kappa score: 0.525\n", "\n", "\n", "------ Step 4/5: Slice 3/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 600, 3\n", "LR fn, tp: 21, 10\n", "LR f1 score: 0.455\n", "LR cohens kappa score: 0.438\n", "LR average precision score: 0.615\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 600, 3\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.847\n", "GB cohens kappa score: 0.840\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 600, 3\n", "KNN fn, tp: 17, 14\n", "KNN f1 score: 0.583\n", "KNN cohens kappa score: 0.568\n", "\n", "\n", "------ Step 4/5: Slice 4/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 593, 10\n", "LR fn, tp: 19, 12\n", "LR f1 score: 0.453\n", "LR cohens kappa score: 0.430\n", "LR average precision score: 0.488\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 600, 3\n", "GB fn, tp: 7, 24\n", "GB f1 score: 0.828\n", "GB cohens kappa score: 0.819\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 597, 6\n", "KNN fn, tp: 17, 14\n", "KNN f1 score: 0.549\n", "KNN cohens kappa score: 0.531\n", "\n", "\n", "------ Step 4/5: Slice 5/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2288 synthetic samples\n" ] }, { "data": { "image/png": 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lJCUlITk5GVevXoWrqytmzpyJ2bNnt6sRBoMBy5Ytw/Lly+Hl5dXm8/TsqW1XO1rCy6u7za8hB3vsF/vUedhjv6zVp1uGtE6nw969e7Ft2zYcPXoUKpUKISEhyM/Px5YtWzBs2LB2N+K9996Dj48PJkyY0K7zFBaWwWgU292epnh5dUdBQanNzi8Xe+wX+9R52GO/Wtun5gK92ZB+9dVXsWvXLuj1eowZMwZvvPEGHnjgAbi7u2PEiBFwcGjVQLxJu3btwrVr15CamgoAKC8vx2uvvYaMjAy8+uqrVrkGEVFn1GzKbt26FQMHDsSTTz6J8PBweHh42KQRe/futfh66tSpmDNnDqZNm2aT6xERdRbN3jjctGkTRo0ahTfffBNjx45FbGwsEhIScPXq1Y5qHxFRlyaIonjLIq5Op0NaWhp27tyJb775BjU1NQCARYsWIS4uDlqt7W/YtQRr0m1jj/1inzoPe+yXNWvSLQrpukpKSrB7927s3LkTJ06cgLOzMx566CG88cYbrTmNTTCk28Ye+8U+dR722K8Ou3HYGDc3Nzz22GN47LHHcOXKFWzfvh0pKSmtPQ0REbVAixaz3LhxA0aj0eLYL7/8AhcXFzz11FPYtWuXTRpHRNTV3TKkN2zYgPHjx+PkyZMWx1euXInw8HCrLQknIqKGmg3plJQUvPPOO1i4cCGGDh1q8b333nsPixYtwsqVK7Fv3z6bNpKIqKtqtib96aefYtmyZZgzZ06D72m1WsyfPx81NTXYsGEDJk6caLNGEhF1Vc2OpLOzszF+/PhmTzBhwgScPXvWqo0iIiJJsyHt4uKCioqKZk9gMBjg5ORk1UYREZGk2ZAODg7G9u3bmz1BcnIyhg8fbtVGERGRpNmQXrBgAT777DO89957DUbU5eXlWLt2LTZv3owFCxbYtJFERE0xHEyFfl4cDAdT5W6KTTR743D48OH4xz/+gRUrVuD999+Hj48PunfvjpKSEpw/fx6enp549913MWrUqI5qLxGRBWNiAsScHBgTE6COiJK7OVZ3yxWH4eHhOHDgANLS0nDq1CmUlJTAw8MD/v7+GDt2LOvRRCQrVUwsjIkJUMXEyt0Um2g2pCsrK/Hmm29i37590Gg0iIiIwAsvvKCYDZWIiNQRUXY5gjZpNqTXrFmDtLQ0xMfHQ6VSYcuWLSguLsbq1as7qHlERF1bsyG9b98+rFq1CqNHjwYAhISEYPbs2dDr9XB0dOyQBhIRdWXNzu7Iz8/HoEGDzF/ffffdEEURhYWFNm8YERHdIqQNBgPUarX5a0EQ4OjoCL1eb/OGERFRC7cqJSIiedxyCl5SUhJcXV3NXxsMBmzfvr3BQ2lnz55t/dYREXVxzYZ0v3798Nlnn1kc69WrF5KSkiyOCYLAkCYisoFmQ/rrr7/uqHYQEVEjWJMmIlIwhjQRkYIxpImIFIwhTUSkYAxpIiIFY0gTESkYQ5qISMEY0kRECsaQJiJSMIY0EZGCMaSJiBSMIU1EpGAMaSIiBWNIExEpGEOaiEjBGNJERArGkCYiUjCGNBGRgikmpH/44QdMmzYNI0eORFRUFLZu3Sp3k4iIZHfLp4V3hLy8PCxatAgrV65EREQEMjMzER8fj/79+yMsLEzu5hERyUYRI+nLly8jOjoaUVFRUKlU8Pf3R0hICE6cOCF304iIZKWIkXRwcDCCg4PNX9+4cQPHjh3D1KlTZWwVEZH8FDGSrqu0tBRPPfUUAgICEBERIXdziIhkJYiiKMrdCJPz589j4cKFGDJkCFatWgUnJye5m0REJCtFlDsA4OjRo1i4cCEee+wxLF26FIIgtPochYVlMBpt9zPHy6s7CgpKbXZ+udhjv9inzsMe+9XaPnl5dW/ye4oI6YsXL2LBggVYsmQJYmNj5W4OEZFiKKImvWXLFpSXl+Odd95BYGCg+ePtt9+Wu2lERLJSxEh6xYoVWLFihdzNICJSHEWMpImIqHEMaSIiBWNIExEpGEOaiEjBGNJERArGkCYiUjCGNBGRgjGkiYgUjCFNRKRgDGkiIgVjSBMRKRhDmoisxnAwFfp5cTAcTG32GLUcQ5qIrMaYmAAxJwfGxIRmj1HLMaSJ6JZaOhpWxcRC8PaGKia22WPUcorYqpSIlK3uaFgdEdXk69QRUQ2+39gxajmOpInoljgalg9H0kR0SxwNy4cjaSIiBWNIExEpGEOaiFqNc587DkOaiFqNc587DkOaiFrFcDAVYlER4ObG2R4dgCFNRK1iTEwASkogeHjYfMZH3bJK3c/1766CbmwI9O+usun1lYBT8IioVVQxsTAmJnTIKNqwbg1wMQeGoiIIHh4Qs87A8MpLgF4P6HQQt30BLHne5u2QE0fSRNQq6ogoOK7f1DHzpsvLgZoaoLxc+qGg1wMVlYBaDQgCEBxi+zbIjCNpIjIzHEw1j5IVsXhFFKU/rxdKf/brD1zMAQwGwLMncDEH+nlxgJ8/xO++AQAIYeHS54WFQFUlhMdmw7GJ0bbi+tsIjqSJuri6td62zNqw9nQ8i/NptdLBmhoYXnkJQlg4cIc34OwMlJUCZWUQc3Igbt0CZJ8DLpyXSiAXc4DiG0B1tfR1E+3sDLNUGNJEXVzdoGrLHh3WDjqLzZyeXgwMGgw4OQE1NVIYX7kMlJYBOh1QdB0oLQGcXQCVGtBoIEyfKY2y1WrAwQEIDpHCed2aBu3sDHuSsNxB1MXVvRHYlj06rH4j0c8fOHMa8PM3t8dwMFW6YVhRCUAENBqpFKLTSX+694AwZIi5D/rMDIhGIwRvb6C0BGJODuDm1iCQO8OeJAxpoi6uvUFl9aDLzJBGxpkZFtcAbs72AKB+ejEMO7cDh76WXqDVwnH9JvPr6/7gMGacBM6chjBpcpO1aSVjSBORojQ1Mq//w8Dwyks336CSyiJNvNaYmNAg9DsT1qSJSFaVe/a06saj6QYggkMArRZC7FyL8P7xXCFWJGXix3PSjJDG6s7N3exU2r4kDGkiktWNl1+BePwYDCvfBHDrG5Gm7wulJdB8f8RcwjCF6/ZDv+LyjUpsP/SrFOZAg3ndhnVrIJ78yVw+aez8SpnxwZAmsiNyjQJvdd3mlnEbbxRJn5QUA7j1jIumvm8K10mZqejfwwWTMlMtwrY9z2mUE2vSRHakpc8i7MjrGg6mQkz4FDAaIW77Agb/AIuas6qHB4xiEYRHYwA0Unuut+CkqRuVplr2mOgwhEX4weCeB2PJBfN16k/ta2pGitJmfAiiaFrS0/kVFpbBaLRdd7y8uqOgoNRm55eLPfarq/apo1bQ1b9Oc9fVz4uDmJEB6HWAuzvQsxdQUACIRqB3H6jKSiEOuMNidkZdummTpcUpd3hDk7SzzX3syNWFrf3vz8ure5Pf40iayI501CjQmJhQu9nRLa6riomF4ZflgB5AcTFQUQGoVNJc599/h7GsFBjuJ82FXrdG2q9DFKWbgmHhUkDX1ABlZfgh+WvsSM9DdLkGo+uM2lsSwEobIbcUa9JE1GqqmFgpSAUVDOvWNFvrVUdESXtumOj10uIT36GArlo6z7EjUkBnnwPyrwLX8oGLOdKSbtNvx1otdpy+jrzuXkjxvd9cqjAtdBGzzijmZp81cSRNRK2if3eVFJ7eA4GcC8ClXIjZ52A4exZA7YITISwcyMyQRrdPL5aO514EDEZAq5VG2G/9FSi+AWH6TIh7dlleqFs3IDAI+PEHoIcX1E8vxpQSNXaevo7JgbcDMEillKIiQFABolExN/usiTXpVrDHOidgn/1in2xHNzYEKCuTvujeHSit06ZBg6XRMCBtJartDsHX11xvNpUl4Ocv7cOhr4GqT2+I/fpDvHQJh537IsUvEtGZBxCaky6dQxQBN3dovv3Rsh2mWnXPXhBuv93qteb21LCtWZNWTLnj9OnTePTRR3HPPfdg8uTJyMiw/eqgeT88Zv4gouZZLCJRqQBHRylAR/hJX4/wAy6cr32DKAJlpRC7u0E3bTJ00ybDsHM7xMyfISYm4PBtw/Hyg0vxo3aAtLdGt25ICfgD8tz6IMUvsjagAWkTpTrt0E18QPphUFMDFP5uHkG3dPphS6bjKWW+tCJCWqfTYeHChXjwwQdx9OhRPPnkk5g3bx7KTD+tZXS88AhW/vwajhcekbspRLKqu4hEiJ0LODlBmD4Tmi1fQHMiE4KzM2A0Wr5JFIH//FsK7+xz0l4b1dWAXo+Uu6OQ59kPe8bNguDtDfXTi+F77SyqHTTwvZYt7WIHAQBweNh9eHH9d/jxXKEUmvlX6zRMhDExoVWh2pLXKmW+tCJC+siRI9Dr9Zg7dy4cHR0xadIkDBkyBLt375a7aThwZQ/yK/Nw4MoeuZtCJCuL0MrMwGGfIPypaiB+SP7avPE++txW710C4OYujbQBwFFj/k70rwfRz9GI2TPHmlcEZt12J5xqdMjqPUgKfAc1oNUiZej9uHKjAtu/SDNf5/CgILw85UUcDo6CKia2VaHaktd26BNomqGIG4dnz57F4MGDLY4NGjQIWVlZNr3u+vu23vI1kf0exIErexDZ70GbtoVI6epPYUs5Uow8bS/sSL+IUVlZQFERhNtvh1h3lAsRqKqS5kZfy5fmSt8Umn0coRfSga3O0FVUAAMGINpzCFJuD0b0qTQppI1GwMMD0cVZSFGrMSnrW0BTDs2+r7Fr/XfIK6nCLm8fhEWEmdsIWNaTAZjr4OYbmZ1oOp4iQrqiogLOzs4Wx1xcXFBZWdmq8/TsqbVmswAAf/CKwB+GRZi/bq7A35nZY7/YJxt6bBri/K9i84Y9eCjrWwgQIVRVwJhxUZqVUVFRW08uKYbQzRWNzlEwGqXXAkBuLkIvXULoyTTL1+TmImzEXQjd8VdpOl7v3tAe+x6Tj27Hjl5+mHwmE14vPmTxloIvEyHmXoT6y88AiBBzL0LMOgPBxQXqLz+D12PTrP93Uo+1/q0UEdKurq6orq62OFZZWQlXV9dWnYezO9rGHvvFPlnPj+cKseNkHqYE9MW9g3uaj4/w6obXg91hzNJB9err0hQ7gxGoqYEQ9z8Qk7dJ+3G4uUOs+/9ln9sg/OEhaRqfk5P0LEJAuhFZU9NoG3R795s/FwsKUPT+RxhVVIRRx/YDPXvhcmCw9MPg0Rio/ANguPY7oO0Ow3/Nkt5jmlGSmQHDf82y+d+j3a04HDx4MD799FOLY9nZ2Xj44YdlaQ8R1dpxMg+Xb1Rix8k83Du4Z6NT04yJCdIDYK/lA4IgBXBVFeDgAOHOO6W5zCoVDg8KxmdR8wCtFrNmeCD007+br6P+2yrLjfwBHPYOrDclTwV49oRYVGSehy3m5kqlFADiti9gzMwASkqkm5E329fS0oYSH0yriBuHoaGhEEURn376KfR6PXbt2oUzZ84gKkoZf0lEXdmUgL7o38MFUwL6Amg4M8L0NTIzoH7tDQi+Q6XnDN7hLX34+UsnGuiDXQ/OwxWDGleKK5Fy3bH2IiP8pJH4jz9Ic6979wEcHJDiF4m8Hrch5e4o6RmGXl5ARTlQUADxu2+k8C+6Xnue4BCpDu3mBrGoSNp9zzT9rwVT85Qy7a4uRYS0RqPBxx9/jH379iEkJAQffPAB1q1bB09PT7mbRtTl3Tu4J/46zc9c6qg7M8JwMFUKSrVa+hPS3s2OS543Py1FTEwALlwAAEwdNxz91Ab0K7+O6JorgFYLzR8mSCsXz2cD1dU47DkEL4+Kw+HbAxD9y0H0vXEV0acPAa4ugFaLw7f74+XxC3G4153SYhZ9nRLJN2kwZpyE4OEBlJTUPjn8Ys4tl6/X75tScMVhK9hjnROwz36xT9bT2EwJ8wNf58VJo+iqSsDZBYK3t3l1oX5eHMT0E7VzpwcNhiZpJ75b8mekaAcjOmM/Qq9kQujVSwr4qioAwMuTliHH83aIgoBn/r0ZoZd/lvb7cHAARo/By33GIU/bC91Kr8OtogTRvxxE6PnjtQ1WqYCBPtLnd3gD338rLYzx8ARuPpy2qR33rMUuVxwSkTLVLQHULweYRp7C9JkWo2vzvGmNRgpIZ2cIYeHQz4tDis+9yHHvi7X3/w8O9/ODeO2aOaABIDrzAEQIqNG4YO34+Tg8epIU0NXVwH/+jehrGeh7Iw8wGJDn1hspIyJw2DsQL09ahsPegdIPhQsXcLjXnXi5zzgcviOgdle9m238IflrLP/rV/gh+eumuq0YirhxSETKVf/BsHU/b2y+sWl0LQBQv7FSCvbubtLG/yo1oouAtffFQYCIFL9IhF46afH+0Jx04EcHrA2fB6GmBrt87kXoL9+ZZ4qE/rgLoVVf1d5U/OUgUgImSrvj+UUCABKDpuKamxccRREpdz2A0AvpEMLCzY/a2vHXr5DnoMXO09cxWoE3C+tiuaMV7PFXaMA++8U+tV9bZzro310F8fNEaQRdUwO4ugIlJbXzplE7a8O38AKy+voi+uf9CL3yC6AzLXYRcLi/n+XMDkdHwMXV/Jitug4PGYXdMcsQLVzDjsx8nHHrDyMEuNRU45lvP5He7+wM9OsP9dOL8R/TbnrDPBGS8qn0Q8WKZRC7m4JHRMrT2COxmqtP/5D8NXacvo7o81cQWlNTO+e5uBimPThMQnPSEZqTjpcnLcPVnv2l0e7Zo9I3XVxwuPcwy4AGpLq03nQuy8FY6JVfELp5hfRF7BJsPnMdlVDDpaZaCncHB0CnBy5K/blv/Sbcd/O9BjdDk4/SUgKOpFvBHkdngH32i31qP/OTUgCon15scaNQ8PYGAIsR6PK/foUcTQ/o1Q7oXVqAmGP/qg1YJydgyJ3AL5nm8x/2DkRi0FRUunaHqK+Bq74SMce3m8M7z60P+pbk4y+73q4z8s5BVk9v+Oafw7E7/FGpcYGLrvZ9AIA+t0H9wgr8vyPFyOtxG/r36YHX3fOkvpSVAVqtuT+2whuHRGRz5hC7OX0NqL1RKHZ3g/hLJqBSmUegU4Z5QlSpUKNS1243etPh24bj5YEPIiFkuvkGX4pfJMpduqNSpUGxqzvy3G9Dil8kDnsHosRJi27VZYjOPAAA0nxptz7YPTQcZ3oPRopfFC559EdhN0/z+wAp+F8OjsV/StR4eOZ49O/TA1MC+kIdEQVN0k4IAwYAJSUwJibI9mT11mK5g4hazHSjUDc2RJptUXQdhldegjHjJEb7B8D4wxZ85j8JIkQpYG/uCZ0Y9DDy3PvgTO9BAASUBHVDzM97kOJ7P3zzz+H4HQHm96T4RaLcqRv6lkirCF+etAy++dKDBK5qe6LYtQdEAILRCDWMcKsoRomT1hz8eW59sPP0dQzrXYrsy9fxa+o2BPt2g+OS5y1ugjb2nEYlYkgTUZPMj72CVP4wB1lwCPDtoZt1Yj3ExAQYtm5BaHU1Qs8eAQQBh31G4uWHnr85GpbKkKZqsgABob8dRuhvhwEAsceSLK5rqken+EUix6M/LngOwDPffoIsLx/sv2sc/C6fQpmL1vwa08jd9PWkgp+xuntf6KDGbt/7EbttObDkeYtl7PDzB86cBgSVRd1daVjuILIz1vw1Xh0RZV69Z7FU+mIOLG4G6vXSyNpEFJEyIhJ57lJ4xpzYiaEF2Yj+ORVDr51D0MWTtfOa6wnNScdfdr2N0Jx0ac60oIJO7YBVEU/i28EhcKrRocxFi7/sehtZXj4422sgVKIBvvnnkBj8CEqctcDvhdCWScvFu1eXQ5g+s/bvZd2aesvYfRV70xDgSJrI7jQ2K6M9TKUB+PlDPy9OCrSyMsBoaPZ9vgXnccGjP3zzzyH0wnGEXqhdFWi6MZjiF1l7w68JgqEGNRoXAECJqzt8r2Wba9X77xoHvdoRlY4uyOozGHluvQEAifdMgquuCq41eYibNR6Og6NrV0e6uZkXtXSGfaUZ0kR2pv7ik/Yy16GnTQYunIch82fAyfmW78vq6Q3BaMT+4ePgWyA9+9BUkjCVJUxhCwAJwdOwe0QEHPXV8KgqhbOuEmf7WD4MRFWjx192vW3+esKpQ9h/1zhMOHUIvgXnUTqqO0SjEYAg1bVV1RZ7jih50UpTGNJEdsZao8P6U/BQWCgtua6utixtNME3/xxO9xkCR4PePPvCNHo2lTPq2n/XOOgcNNA5aFDl5AqDSt3wpPWOxR5Lqq1nd+8O/LwHKUPD4Zv3G7JuG4LorG9hOKg1/510pnA2YUgTUaMM69ZID49VqaXPi2+06v1ZfQbDRVcJUVAhOvMAsrx8cMFzgHmmRl2HvQPhoq9ElYMGRggwqFRwL7+OUtceCL7wE/qV5GP3iAh0ry7DYe/ABgF/eOi9SBkyFiXaHihXOwF9Bfxl99uAUYThrfOdcgRtwpAmIrO6o2eUlUl/Gg1SWLdSdOYBJAZNhekGY1afwdJDZuuVMACpDGIU1HCu0aHiZv250kmLLzcsML9Gqjk3rGMf9g7E2pBZEEQjPCuK0bfsBqJ/+VpaZVhTAxT+DrHwdxiKijplSHN2B1EX1NgMEMPBVGnO8IULwIXzje6R0RSLXehuCs1Jh1t1OcqdukmrBfPPodpBA21lWYPXRmceQN+SfPhdPgXTdD2nGp3F60zvrz8ST/GLhAARoqDCrOP/kkopF45LDwhwdpa2Lr0Z1p0RQ5qoC2rsCSTGxARp8YnGUdpi1FEDuLtL37zF80brzlWuyxS+0ZkHzCPpzP53NXitadpdmYsW3XSVcNVVwr2y2OJ1TY3EozMPwPv6JUw4dci8YhEAkJsrbYFq2rSpBXV0JWJIE3VBjT2BRBUTKz366tEYoF9/KZhFSKPRkNGWJ1Bb3sCrG8ZA7cgagMWc574l+Zhw6pDFawFpZsesOeuQ494XnuU38My3nyDm+HaL19W/hokp4M3lEP8JUpvde0gvcHGVRtOjx1jhb67jcYOlVrDHTXsA++wX+9R2+nlx0r4cdTbit9RwF7r66m+QdCuxsWvMtejhV7Na9J76zPtLF/yMsI/ekco3K98ECq4BTk4QRvjZ/IksJtyqlIhsRhUTC8OyJY1/09FRGpXeLB00eJr3Tb755yxmctR9HQBzjTqrz2BEZx7AhFOHzHOkTftw3GqRS32m7U/h7Gxewm545SVpH2udTtGrCpvDcgeRHWrN0nDTa/XvrpIeewVAiJ0rhbHjzcdfAdJsCc+eUhmhdx/A1bXJWnT9+nHd15k+33/XOPOx2GNJ+Gzj0/AuzjPfaGwRlUr6MLVPqwUcNeZauzB9pvTYrNi5nXJmB8CRNJFdas3ScNNrceY04OxinlNsuPkwVyEsHMjMgHjpEpB/tfaNgtDoykEADY7X/7r+SBrAzS1Ku0FbXd7gfI1SqYBuWql2Xl4GYfpMqPwDLFZbOi55Hrj5yKzOiiFNZIdaszS87t4cyMwA/PxheGm5VJN2coLKPwDqJc9Ly8LrEsXaEkM9puOmG4jRmQfwl11vIyF4mnkZd2M735U7adG3JL/hYpX6ZRW1GggLh1BaYl6k0tbHfSkdyx1EdkgdEQXH9ZtaFFam16r8AyAWFUnPJ6y6OV2tuhqGdWukskl5+S3PVX++dP1yyP67xqHS0Rn77xrX4L1Nzd6ARoMU/wnmHfUAAIIAobTEoo+NTSu0BwxpIjvV2i1LjYkJ0srCqipYzN7IuyLdgCsokEoMgtDkOUyh/FnQw3h22qu4qu1lUb6YcOoQXPRVmHDqUIP31t2i1IJOh+iM/ehbnI/oM99I9fA7vBv8ltDYtEJ7wHIHkZ1q7ZalqphYGI4fa/iNysraz93cgcoKaf/oRphqzyVO3ZDnfhsA4LZrv5uD17fgPLL6DDbvitdSoTnpCM0/BfUbKxv0pW6Zo6Om2HUkjqSJ7FRjI8vmRtfGjJO3PmlJcZMBDdSOhmOOb4d7xQ2ojQaLZdxNzQax4OhY+7mLi7QwpXefRgMasN8yhwlDmshONVaXrh9odUNbtELI1V1peFtZIRyNNdh/1zhzjbrJunNdNTW1n1dWAl5e0OxPM98c1E2bDN20yeYfNPZa5jBhuYOoC6k/68Owbo30NPCzvzU7Qm6p+s8bXHv//0AQjead65qaDWKh/iLo3FxzSUMsKpI2gDIaYFi3plPvE91SHEkT2bH65Y1GZ30YRaC45Tve1VV/NkfdnepCc9LxzLefwLvocsvmPdelUll8bnhpOcSsLOlrjaPl92Hd5zoqDUOayI7dql6rfnox4OpSG3oDBrTq/PVrzPVXGppq1ACafPBsA27ugFdvaQUhID0NpqoKEI1QP70Y6jdWQggcKbX9Fv20h/BmSBPZsVvVa9URUVC/9oa0aq+7G1BUJN2sa6H6Neamas4tumFY3x3elm197Q1zaaP+bwNN9dMebipyF7xWsMed1QD77Bf71DRTfRd+/hC/+wZAnaXfVVXAqV+B+8dBPXkqDM8926Zr1F9Z2NRGTE0TAJUAeHhIz1Yc4QfNli9a3Q65ViFyFzwiajOLvTpubkcqfvcNBA8P4NxZ6cbdsSNQr14Lg0ollRtaqe7KwthjSS27YWhBlGrl1dXQ/PRrq69vYg83FVnuIOrkWlt3NZUGhOkzpZLCHd5AWRnEkz9JqwkFAfAeKO2IV29zfzhqWnSN5lYWNt0wFTBosPTh3kPaA3r6zJa/306x3NEK9vgrNGCf/epKfdLPi4OYkwPB27vNK+500yYDF3Okm3WOGqC8TNphrqzUckqcs7P0Z5MPBGgDUz28Wzeon15sHunX709n2kDJmuUOjqSJOjlrLOZQP70YQsA90qOzRKP0jEPRCISPl/ZoHuEn7cv8aAzUb6yURrv1R9lt4aiBxt8fmn1fQ5O0EwCkudBubnZ5E7AtWJMm6uSsUXetew5DnT2ZmzqvOiIK+ndXQdy4oWUXEATLEblKBdw1HKishOF6IXDzSSrGxASgpASCt3eDa7dm+1V7wpAmIgstDv3MDMDBEajRS/OrCwoaL4MIgjTv+Vq+9LWDAzTHMgDcLNXkXoR4cxOo5oLYHm4CtgVDmojaRBUTCyNqR7hiZRVgMEjLy1UqYKAPUFYGXC+UNmZydgF01RBmx1mcQ/3lZzD81ywAXTeIm8OQJqI2qR+o0tzryUBmRoOnpdSdk63yD7A4h9dj0+zuJq81KSakN27ciE2bNuHGjRvw8fHBiy++iODgYLmbRUQt0NQIuO5xfWZGq/a3JokiZnfs378f//znP/Hhhx/i6NGjmDVrFhYsWIDr16/L3TQishJ731LUVhQR0gUFBXjyyScxZMgQqFQqTJ8+HWq1GmfOnJG7aURkJa157iLV6rByh06nQ3Ej2yEKgoDZs2dbHDt69CgqKipw5513dlTziIgUqcNWHB4+fBhxcXENjqvVavz6a+3a/KysLDz++OOYM2cO5s+f3xFNIyJSLEUtC09LS8MLL7yA+fPn44knnmj1+7ksvG3ssV/sU+dhj/2yy13wNm7ciNWrV+Nvf/sbJk6cKHdziIgUQREhvXv3brz77rvYuHEjAgICbv0GIqIuQhEh/fHHH0On02Hu3LkWx9955x2MHz9enkYRESmAIkI6OTlZ7iYQESmSIuZJExFR4xjSREQKxpAmIlIwRdSkrUWlEuziGnKwx36xT52HPfbLWn1S1GIWIiKyxHIHEZGCMaSJiBSMIU1EpGAMaSIiBWNIExEpGEOaiEjBGNJERArGkCYiUjCGNBGRgjGk2+jkyZMYMWIELl26JHdTrGLjxo2IiIhAUFAQZsyYgWPHjsndpDY5ffo0Hn30Udxzzz2YPHkyMjIy5G5Su/3www+YNm0aRo4ciaioKGzdulXuJllNSUkJxo0bh6SkJLmbYhXXrl3DwoULERQUhDFjxmD16tXtP6lIrVZWViZOmDBB9PX1FXNzc+VuTrvt27dPHDt2rPjbb7+JBoNB/Oqrr8SRI0eKhYWFcjetVaqrq8Xx48eLn3zyiajT6cSUlBQxODhYLC0tlbtpbXblyhUxMDBQ3L9/v2gwGMSTJ0+Ko0aNEr/99lu5m2YVf/zjH8Vhw4aJ27Ztk7spVjF9+nTxz3/+s1hVVSVevHhRDA8PF3fs2NGuc3Ik3Qavv/46JkyYIHczrKagoABPPvkkhgwZApVKhenTp0OtVuPMmTNyN61Vjhw5Ar1ej7lz58LR0RGTJk3CkCFDsHv3brmb1maXL19GdHQ0oqKioFKp4O/vj5CQEJw4cULuprVbcnIyysrK4OvrK3dTrOLkyZPIzc3Fn/70Jzg5OWHAgAFISEhAaGhou85rV7vgWYNOp0NxcXGD44IgoFevXti7dy8uXryI5cuX46OPPpKhhW3TXL9mz55tcezo0aOoqKjAnXfe2VHNs4qzZ89i8ODBFscGDRqErKwsmVrUfsHBwQgODjZ/fePGDRw7dgxTp06VsVXtl5ubi7Vr12Lr1q2Ij4+XuzlWkZmZCV9fX6xduxZJSUlwcnJCTEwMHn/88XadlyFdT3p6OuLi4hocV6vVSEtLw1tvvYVNmzZBpepcv4Q0169ff/3V/HVWVhaWLFmCZ599Fr169erIJrZbRUUFnJ2dLY65uLigsrJSphZZV2lpKZ566ikEBAQgIiJC7ua0mcFgwLJly7B8+XJ4eXnJ3RyrKS4uxvHjxxESEoKDBw8iOzsb8fHx8PLywuTJk9t8XoZ0PaGhoY3+mi+KIubOnYvFixfj9ttvR0lJiQyta7um+lVXWloaXnjhBcyfPx/z58/voJZZj6urK6qrqy2OVVZWwtXVVaYWWc/58+excOFCDBkyBKtWrep0g4S63nvvPfj4+NhVyRAANBoNtFotFi1aBAAYNmwYZsyYgdTU1HaFdOf9l+5geXl5OHHiBF5//XUEBwebn2I+ZcoU7Ny5U+bWtd/GjRuxdOlSvP7663jiiSfkbk6bDB48GOfPn7c4lp2djSFDhsjUIus4evQoZs6cicjISKxZswZOTk5yN6lddu3ahX379plLOVlZWXjttdfw6quvyt20dhk0aBAqKyuh0+nMxwwGQ/tPbJ17ml1PcXGx3czu2LVrlxgQECD+9NNPcjelXaqrq8X777/fYnZHYGBgp5ulUldOTo4YGBgobtq0Se6m2MyUKVPsYnZHVVWVeP/994v/+7//K1ZXV4unT58WR48eLe7du7dd5+VImvDxxx9Dp9Nh7ty5CAwMNH+kpaXJ3bRW0Wg0+Pjjj7Fv3z6EhITggw8+wLp16+Dp6Sl309psy5YtKC8vxzvvvGPxb/P222/L3TSqx8nJCZs3b0Zubi7CwsIQHx+P+Ph4TJw4sV3n5eOziIgUjCNpIiIFY0gTESkYQ5qISMEY0kRECsaQJiJSMIY0EZGCMaTJrj3wwAMYOnSo+WP48OEYP348Vq5ciYqKCvPrfv31VyxevBhjxoxBYGAgpk+f3uRK0iNHjmDo0KH485//3Oj3z507h9jYWNxzzz34wx/+gP3799ukb9Q1MKTJ7i1duhTff/89vv/+e6SlpeHNN9/Ejh078MYbbwAAvvnmG8yaNQt9+/bFP//5TyQnJ2Py5MlYsWIF1q9f3+B8O3bswMCBA7Fr1y5UVVVZfK+6uhrx8fHw8fHBtm3bMHPmTCxduhSnTp3qkL6SHbLKekgihRo/fryYkJDQ4PgHH3wgBgUFiWVlZeLo0aPF//u//2vwmg8//FD09/e3WFZeXV0tBgcHi0lJSeLdd98tJicnW7wnOTlZHDNmjKjX683HnnnmGXHFihXW6xR1KRxJU5ekVquh0WiQlpaG0tJSzJ07t8FrYmJisGHDBri5uZmPpaWloaysDOHh4bjvvvuwbds2i/ecOHEC99xzDxwcajeYHDVqFI4fP26zvpB9Y0hTl2I0GpGRkYHNmzcjMjISp06dgo+PD7RabYPXarVaBAUFWQTujh07MHLkSHh6eiIqKgpHjx5Fbm6u+fvXrl1Dnz59LM7j5eWF/Px823WK7BpDmuze3/72N/PGRHfffTdiYmLg7++P559/HiUlJY0GdGOKi4vxzTffICoqCoB0U1KtVluMpisrK6HRaCzep9FoLLavJGoNbvpPdm/BggWYMmUKAMDR0RG9evUyB6mHh0eLH+CwZ88e6PV682b1PXr0QEhICJKTk7F48WKoVCo4Ozs3CGSdTtfgiTFELcWRNNk9Dw8PeHt7w9vbG/369bMY6fr7++P8+fMoKytr8L7S0lLExsbi559/BiCVOgAgMjISw4cPx/Dhw/Hjjz/i6tWr+P777wEAffr0QUFBgcV5CgoKGpRAiFqKIU1d2tixY+Hp6YlPPvmkwfe2bt2K9PR09O/fH5cvX8aJEyewaNEi/Otf/zJ/JCUloVu3buaSx8iRI5Geno6amhrzeY4ePYrAwMAO6xPZF5Y7qEtzdnbGq6++ij/+8Y8oLy/HI488AgcHB+zfvx/r1q3DsmXL4Onpiffffx9OTk6Ii4uzmO0BAI888gg+//xzFBUVYcKECXjnnXfwpz/9CfHx8fjuu+9w6NAhfPnllzL1kDo7jqSpy4uMjMT69evx22+/Yc6cOZgxYwa+/vprvPXWW5gzZw4AYOfOnXjooYcaBDQAzJ49GzU1Ndi5cydcXV3x0Ucf4cKFC3jkkUfwxRdfYPXq1Rg2bFhHd4vsBJ/MQkSkYBxJExEpGEOaiEjBGNJERArGkCYiUjCGNBGRgjGkiYgUjCFNRKRgDGkiIgVjSBMRKdj/B5FNOEQZPwJxAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 592, 8\n", "LR fn, tp: 19, 8\n", "LR f1 score: 0.372\n", "LR cohens kappa score: 0.351\n", "LR average precision score: 0.437\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 596, 4\n", "GB fn, tp: 10, 17\n", "GB f1 score: 0.708\n", "GB cohens kappa score: 0.697\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 593, 7\n", "KNN fn, tp: 12, 15\n", "KNN f1 score: 0.612\n", "KNN cohens kappa score: 0.597\n", "\n", "\n", "====== Step 5/5 =======\n", "-> Shuffling data\n", "-> Spliting data to slices\n", "\n", "------ Step 5/5: Slice 1/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 588, 15\n", "LR fn, tp: 19, 12\n", "LR f1 score: 0.414\n", "LR cohens kappa score: 0.386\n", "LR average precision score: 0.481\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 598, 5\n", "GB fn, tp: 10, 21\n", "GB f1 score: 0.737\n", "GB cohens kappa score: 0.725\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 4\n", "KNN fn, tp: 17, 14\n", "KNN f1 score: 0.571\n", "KNN cohens kappa score: 0.555\n", "\n", "\n", "------ Step 5/5: Slice 2/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 598, 5\n", "LR fn, tp: 20, 11\n", "LR f1 score: 0.468\n", "LR cohens kappa score: 0.450\n", "LR average precision score: 0.530\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 601, 2\n", "GB fn, tp: 11, 20\n", "GB f1 score: 0.755\n", "GB cohens kappa score: 0.744\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 599, 4\n", "KNN fn, tp: 18, 13\n", "KNN f1 score: 0.542\n", "KNN cohens kappa score: 0.525\n", "\n", "\n", "------ Step 5/5: Slice 3/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 593, 10\n", "LR fn, tp: 18, 13\n", "LR f1 score: 0.481\n", "LR cohens kappa score: 0.459\n", "LR average precision score: 0.553\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 598, 5\n", "GB fn, tp: 14, 17\n", "GB f1 score: 0.642\n", "GB cohens kappa score: 0.626\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 598, 5\n", "KNN fn, tp: 18, 13\n", "KNN f1 score: 0.531\n", "KNN cohens kappa score: 0.513\n", "\n", "\n", "------ Step 5/5: Slice 4/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2289 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 601, 2\n", "LR fn, tp: 22, 9\n", "LR f1 score: 0.429\n", "LR cohens kappa score: 0.414\n", "LR average precision score: 0.545\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 599, 4\n", "GB fn, tp: 6, 25\n", "GB f1 score: 0.833\n", "GB cohens kappa score: 0.825\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 601, 2\n", "KNN fn, tp: 14, 17\n", "KNN f1 score: 0.680\n", "KNN cohens kappa score: 0.668\n", "\n", "\n", "------ Step 5/5: Slice 5/5 -------\n", "-> Reset the GAN\n", "-> Train generator for synthetic samples\n", "Epoch 1/3\n", "Epoch 2/3\n", "Epoch 3/3\n", "-> create 2288 synthetic samples\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "-> test with 'LR'\n", "LR tn, fp: 590, 10\n", "LR fn, tp: 21, 6\n", "LR f1 score: 0.279\n", "LR cohens kappa score: 0.255\n", "LR average precision score: 0.375\n", "\n", "-> test with 'GB'\n", "GB tn, fp: 594, 6\n", "GB fn, tp: 10, 17\n", "GB f1 score: 0.680\n", "GB cohens kappa score: 0.667\n", "\n", "-> test with 'KNN'\n", "KNN tn, fp: 597, 3\n", "KNN fn, tp: 17, 10\n", "KNN f1 score: 0.500\n", "KNN cohens kappa score: 0.486\n", "\n", "### Exercise is done.\n", "\n", "-----[ LR ]-----\n", "maximum:\n", "LR tn, fp: 601, 15\n", "LR fn, tp: 26, 15\n", "LR f1 score: 0.556\n", "LR cohens kappa score: 0.536\n", "LR average precision score: 0.658\n", "\n", "\n", "average:\n", "LR tn, fp: 594.64, 7.76\n", "LR fn, tp: 20.28, 9.92\n", "LR f1 score: 0.411\n", "LR cohens kappa score: 0.390\n", "LR average precision score: 0.493\n", "\n", "\n", "minimum:\n", "LR tn, fp: 588, 2\n", "LR fn, tp: 16, 5\n", "LR f1 score: 0.227\n", "LR cohens kappa score: 0.204\n", "LR average precision score: 0.343\n", "\n", "\n", "-----[ GB ]-----\n", "maximum:\n", "GB tn, fp: 603, 9\n", "GB fn, tp: 14, 25\n", "GB f1 score: 0.885\n", "GB cohens kappa score: 0.880\n", "\n", "\n", "average:\n", "GB tn, fp: 598.04, 4.36\n", "GB fn, tp: 8.32, 21.88\n", "GB f1 score: 0.774\n", "GB cohens kappa score: 0.764\n", "\n", "\n", "minimum:\n", "GB tn, fp: 594, 0\n", "GB fn, tp: 4, 17\n", "GB f1 score: 0.642\n", "GB cohens kappa score: 0.626\n", "\n", "\n", "-----[ KNN ]-----\n", "maximum:\n", "KNN tn, fp: 602, 7\n", "KNN fn, tp: 22, 17\n", "KNN f1 score: 0.680\n", "KNN cohens kappa score: 0.668\n", "\n", "\n", "average:\n", "KNN tn, fp: 598.4, 4.0\n", "KNN fn, tp: 16.36, 13.84\n", "KNN f1 score: 0.574\n", "KNN cohens kappa score: 0.559\n", "\n", "\n", "minimum:\n", "KNN tn, fp: 593, 1\n", "KNN fn, tp: 12, 9\n", "KNN f1 score: 0.400\n", "KNN cohens kappa score: 0.381\n", "\n" ] } ], "source": [ "exercise = Exercise(shuffleFunction=shuffler, numOfShuffles=5, numOfSlices=5)\n", "exercise.run(gan, data)\n", "exercise.saveResultsTo(f\"{datasetName}-{ganName}.csv\")" ] }, { "cell_type": "code", "execution_count": null, "id": "84f8c688", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }