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Ensemble_bm.ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Ensemble_bm.ipynb","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"hSxMF0ZdPDcH"},"source":["# Ensemble"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cIAvz87XOUVp","executionInfo":{"status":"ok","timestamp":1613064579262,"user_tz":-60,"elapsed":4389,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"7d4ee369-85c9-457d-a2f7-14401d67109d"},"source":["!pip install import-ipynb"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Collecting import-ipynb\n","  Downloading https://files.pythonhosted.org/packages/63/35/495e0021bfdcc924c7cdec4e9fbb87c88dd03b9b9b22419444dc370c8a45/import-ipynb-0.1.3.tar.gz\n","Building wheels for collected packages: import-ipynb\n","  Building wheel for import-ipynb (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for import-ipynb: filename=import_ipynb-0.1.3-cp36-none-any.whl size=2976 sha256=f299ae3c725d7c35898563a06c7c3956c8f4d51587311466c241d17099a775a2\n","  Stored in directory: /root/.cache/pip/wheels/b4/7b/e9/a3a6e496115dffdb4e3085d0ae39ffe8a814eacc44bbf494b5\n","Successfully built import-ipynb\n","Installing collected packages: import-ipynb\n","Successfully installed import-ipynb-0.1.3\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"F85lDRArPLLU","executionInfo":{"status":"ok","timestamp":1613064604387,"user_tz":-60,"elapsed":19101,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"17142c73-8c0c-4ba8-c168-d07e08fc7784"},"source":["from google.colab import drive\r\n","drive.mount('/content/gdrive')"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Mounted at /content/gdrive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9RFsmJWwPL48","executionInfo":{"status":"ok","timestamp":1613064606065,"user_tz":-60,"elapsed":434,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"0f245a77-127c-4d55-a5b9-da339c0027c2"},"source":["%cd '/content/gdrive/MyDrive/Colab'"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/content/gdrive/MyDrive/Colab\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"LGQ8qdIkPVR0","executionInfo":{"status":"ok","timestamp":1613064610849,"user_tz":-60,"elapsed":3043,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"5cb93c50-033c-4dd5-f5fa-2e93c18ad516"},"source":["import import_ipynb\r\n","import os\r\n","import sklearn.metrics as metrics\r\n","import Utils as utils\r\n","import tensorflow as tf\r\n","import numpy as np"],"execution_count":null,"outputs":[{"output_type":"stream","text":["importing Jupyter notebook from Utils.ipynb\n","Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"lHYNgo8GGMa6"},"source":["## Models"]},{"cell_type":"code","metadata":{"id":"ykpRXU2ZPcHN"},"source":["#Load best models\r\n","\r\n","scratch = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di scratch_bm_64.h5')\r\n","\r\n","inception = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di inception_bm_16.h5')\r\n","\r\n","vgg = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di vgg_bm_32.h5')"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"W8gky2Q4GOSv"},"source":["## Data preprocessing"]},{"cell_type":"code","metadata":{"id":"hUWbt7YEBUYR"},"source":["test_images, test_labels = utils.load_test()\r\n","test_dataset, test_lab = utils.binarize(test_images, test_labels, 'benign_malignant')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"kfwHbP_7Eeg1"},"source":["#Scratch\r\n","test_scratch = utils.rescale(test_dataset)\r\n","test_scratch = np.expand_dims(test_scratch, axis=3)\r\n","\r\n","#Inception \r\n","\r\n","test_inception = utils.rescale(test_dataset)\r\n","test_inception = [np.stack((test_inception[i],)*3, axis=2) for i in range (len(test_inception))]\r\n","test_inception = np.array(test_inception)"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"0gqoBD1WGQNj"},"source":["## Evaluation"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WeIwRs9xSZPc","executionInfo":{"status":"ok","timestamp":1613064724488,"user_tz":-60,"elapsed":9806,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"d72dc78d-201c-4f37-8af6-ab787234ce9f"},"source":["#Scratch\r\n","\r\n","predicted_s = scratch.predict(test_scratch, verbose=1)\r\n","pred_s = [0 if x <=0.5 else 1 for x in predicted_s]\r\n","\r\n","#Inception \r\n","predicted_i = inception.predict(test_inception, verbose=1)\r\n","pred_i = [0 if x <=0.5 else 1 for x in predicted_i]\r\n","\r\n","#Vgg\r\n","predicted_v = vgg.predict(test_inception, verbose=1)\r\n","pred_v = [0 if x <=0.5 else 1 for x in predicted_v]"],"execution_count":null,"outputs":[{"output_type":"stream","text":["11/11 [==============================] - 7s 16ms/step\n","11/11 [==============================] - 1s 24ms/step\n","11/11 [==============================] - 1s 73ms/step\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"drZwY0OueShA","executionInfo":{"status":"ok","timestamp":1613064726433,"user_tz":-60,"elapsed":420,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"23978bb8-225c-4a3c-aa09-f9c1838e6b83"},"source":["#Compute AUC Score\r\n","\r\n","score_scratch = metrics.roc_auc_score(test_lab, pred_s, average=\"weighted\")\r\n","score_inception = metrics.roc_auc_score(test_lab, pred_i, average=\"weighted\")\r\n","score_vgg = metrics.roc_auc_score(test_lab, pred_v, average=\"weighted\")\r\n","\r\n","print(\"Scratch Score: \", score_scratch)\r\n","print(\"Inception Score: \", score_inception)\r\n","print(\"VGG Score: \", score_vgg)\r\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Scratch Score:  0.6567732115677322\n","Inception Score:  0.7068844397611522\n","VGG Score:  0.6661983374312141\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3w398TXsmai2","executionInfo":{"status":"ok","timestamp":1613064782379,"user_tz":-60,"elapsed":417,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"149171d6-0a08-4a94-a8ef-1c0683f57a1c"},"source":["predicted_s = np.reshape(predicted_s, -1)\r\n","predicted_i = np.reshape(predicted_i, -1)\r\n","predicted_v = np.reshape(predicted_v, -1)\r\n","\r\n","ensemble_results = 0.33* (predicted_s*score_scratch + predicted_i*score_inception + predicted_v*score_vgg)\r\n","ensemble_results = [0 if x <=0.5 else 1 for x in ensemble_results]\r\n","\r\n","utils.evaluate_classifier(test_lab, ensemble_results)\r\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Performances: \n","Accuracy:  0.6845238095238095\n","Precision:  0.7081065759637188\n","Recall:  0.6845238095238095\n","F1-score:  0.6031503710424082\n","AUC:  0.5569605432619131\n"],"name":"stdout"}]}]}

Ensemble_mc.ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Ensemble_mc.ipynb","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"hSxMF0ZdPDcH"},"source":["# Ensemble"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cIAvz87XOUVp","executionInfo":{"status":"ok","timestamp":1613065166552,"user_tz":-60,"elapsed":5233,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"a29c371c-9235-430b-8270-7e2948d1f9d2"},"source":["!pip install import-ipynb"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Collecting import-ipynb\n","  Downloading https://files.pythonhosted.org/packages/63/35/495e0021bfdcc924c7cdec4e9fbb87c88dd03b9b9b22419444dc370c8a45/import-ipynb-0.1.3.tar.gz\n","Building wheels for collected packages: import-ipynb\n","  Building wheel for import-ipynb (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for import-ipynb: filename=import_ipynb-0.1.3-cp36-none-any.whl size=2976 sha256=284595d83ff1d63c7e431a59c2a1fa16f084e9c4c3b22be5d2428dbcf496c2ba\n","  Stored in directory: /root/.cache/pip/wheels/b4/7b/e9/a3a6e496115dffdb4e3085d0ae39ffe8a814eacc44bbf494b5\n","Successfully built import-ipynb\n","Installing collected packages: import-ipynb\n","Successfully installed import-ipynb-0.1.3\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"F85lDRArPLLU","executionInfo":{"status":"ok","timestamp":1613065186963,"user_tz":-60,"elapsed":18654,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"2397a3aa-6171-4c33-ed46-36986cd429f1"},"source":["from google.colab import drive\r\n","drive.mount('/content/gdrive')"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Mounted at /content/gdrive\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9RFsmJWwPL48","executionInfo":{"status":"ok","timestamp":1613065188490,"user_tz":-60,"elapsed":435,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"337a701c-b30a-4a64-b438-2857865a6944"},"source":["%cd '/content/gdrive/MyDrive/Colab'"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/content/gdrive/MyDrive/Colab\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"LGQ8qdIkPVR0","executionInfo":{"status":"ok","timestamp":1613065192840,"user_tz":-60,"elapsed":3034,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"36b17db6-3cab-4978-9e60-333abd19acee"},"source":["import import_ipynb\r\n","import os\r\n","import sklearn.metrics as metrics\r\n","import Utils as utils\r\n","import tensorflow as tf\r\n","import numpy as np"],"execution_count":null,"outputs":[{"output_type":"stream","text":["importing Jupyter notebook from Utils.ipynb\n","Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"7RkOjP7gF-jJ"},"source":["# Models"]},{"cell_type":"code","metadata":{"id":"ykpRXU2ZPcHN"},"source":["#Load best models\r\n","\r\n","scratch = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di scratch_mc_32.h5')\r\n","\r\n","inception = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di inception_mc_16_3.h5')\r\n","\r\n","vgg = tf.keras.models.load_model('/content/gdrive/MyDrive/Colab/bestmodels/Copia di vgg_mc_64_2.h5')"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"1GvFdKoAGCL9"},"source":["## Data preprocessing"]},{"cell_type":"code","metadata":{"id":"hUWbt7YEBUYR"},"source":["test_images, test_labels = utils.load_test()\r\n","test_dataset, test_lab = utils.binarize(test_images, test_labels, 'mass_calcification')"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"kfwHbP_7Eeg1"},"source":["#Scratch\r\n","test_scratch = utils.rescale(test_dataset)\r\n","test_scratch = np.expand_dims(test_scratch, axis=3)\r\n","\r\n","#Inception \r\n","\r\n","test_inception = utils.rescale(test_dataset)\r\n","test_inception = [np.stack((test_inception[i],)*3, axis=2) for i in range (len(test_inception))]\r\n","\r\n","test_inception = np.array(test_inception)"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"sLGc7X9rGF_k"},"source":["## Evaluation"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WeIwRs9xSZPc","executionInfo":{"status":"ok","timestamp":1613065285986,"user_tz":-60,"elapsed":9935,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"e21ba781-9fc4-4cca-9e32-0cb7a750174d"},"source":["#Scratch\r\n","\r\n","predicted_s = scratch.predict(test_scratch, verbose=1)\r\n","pred_s = [0 if x <=0.5 else 1 for x in predicted_s]\r\n","\r\n","#Inception \r\n","predicted_i = inception.predict(test_inception, verbose=1)\r\n","pred_i = [0 if x <=0.5 else 1 for x in predicted_i]\r\n","\r\n","#Vgg\r\n","predicted_v = vgg.predict(test_inception, verbose=1)\r\n","pred_v = [0 if x <=0.5 else 1 for x in predicted_v]"],"execution_count":null,"outputs":[{"output_type":"stream","text":["11/11 [==============================] - 7s 17ms/step\n","11/11 [==============================] - 1s 24ms/step\n","11/11 [==============================] - 1s 73ms/step\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"drZwY0OueShA","executionInfo":{"status":"ok","timestamp":1613065291585,"user_tz":-60,"elapsed":533,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"c29c9fad-f208-4c12-b845-b6f82ca1f30f"},"source":["#Compute AUC Score\r\n","\r\n","score_scratch = metrics.roc_auc_score(test_lab, pred_s, average=\"weighted\")\r\n","score_inception = metrics.roc_auc_score(test_lab, pred_i, average=\"weighted\")\r\n","score_vgg = metrics.roc_auc_score(test_lab, pred_v, average=\"weighted\")\r\n","\r\n","print(\"Scratch Score: \", score_scratch)\r\n","print(\"Inception Score: \", score_inception)\r\n","print(\"VGG Score: \", score_vgg)\r\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Scratch Score:  0.8716685051417998\n","Inception Score:  0.9142974059708928\n","VGG Score:  0.8764188876632388\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3w398TXsmai2","executionInfo":{"status":"ok","timestamp":1613065299933,"user_tz":-60,"elapsed":397,"user":{"displayName":"Lorenzo Barigliano","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhJz2zmPaDWvwZTBDgVWH7MHpMbI7nlRMYGlzSK=s64","userId":"15301674381195144039"}},"outputId":"9473585c-d1ea-4468-fa0b-87f8ec72eeba"},"source":["predicted_s = np.reshape(predicted_s, -1)\r\n","predicted_i = np.reshape(predicted_i, -1)\r\n","predicted_v = np.reshape(predicted_v, -1)\r\n","\r\n","ensemble_results = 0.33* (predicted_s*score_scratch + predicted_i*score_inception + predicted_v*score_vgg)\r\n","ensemble_results = [0 if x <=0.5 else 1 for x in ensemble_results]\r\n","\r\n","utils.evaluate_classifier(test_lab, ensemble_results)\r\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Performances: \n","Accuracy:  0.9017857142857143\n","Precision:  0.9017615486365487\n","Recall:  0.9017857142857143\n","F1-score:  0.9017656111542661\n","AUC:  0.9011671351812973\n"],"name":"stdout"}]}]}