{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import numpy as np \nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.metrics import f1_score, accuracy_score\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"CSV dosyasını okuma"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"df = pd.read_csv(\"/kaggle/input/digit-recognizer/train.csv\")\ndf.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Label Droplayıp, Label Üzerindeki Değerleri Alma"},{"metadata":{"trusted":true},"cell_type":"code","source":"sample = df.iloc[4].drop(\"label\")\nsample = sample.values.reshape(28,28)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Seçilen Label Altında Bulunan Değeri Görüntüleme"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.matshow(sample, cmap=\"gray\")\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"y = df[\"label\"].values\nx = df.drop(\"label\", axis=1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(\"Shape of X: \", x.shape)\nprint(\"Shape of Y: \", y.shape)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"X ve Y Değerlerinin Eğitilmesi"},{"metadata":{"trusted":true},"cell_type":"code","source":"x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.2, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"rf_model = RandomForestClassifier()\nrf_model.fit(x_train, y_train)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"predictions = rf_model.predict(x_test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Eğitilen Parametrelerin Değerini Alma"},{"metadata":{"trusted":true},"cell_type":"code","source":"print(f1_score(y_test, predictions, average=\"weighted\"))\nprint(\"Accuracy:\", accuracy_score(y_test, predictions))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"y_test[15]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"Seçilen Labellar Üzerinde Bulunan Değerleri Görüntüleme ve Eğitilen Konu Altında Değerin Tahminine Ulaşma"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.matshow(x_test.iloc[1222].values.reshape(28, 28), cmap=\"gray\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"rf_model.predict(x_test.iloc[1222].values.reshape(1, -1))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}