{"metadata":{"kernelspec":{"name":"conda-env-anaconda-2024.02-py310-py","display_name":"anaconda-2024.02-py310","language":"python"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"id":"909cc69c-555b-4091-aecf-3673ae2b732f","cell_type":"code","source":"import pandas as pd\nfrom sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay\nimport matplotlib.pyplot as plt","metadata":{"trusted":true},"outputs":[],"execution_count":1},{"id":"d1f52c6d-1f27-4275-a0d1-0933ae4a6227","cell_type":"code","source":"iris = load_iris()\nX = iris.data\ny = iris.target","metadata":{"trusted":true},"outputs":[],"execution_count":2},{"id":"6bf88d4e-a5a9-436c-a8a5-cd77259913da","cell_type":"code","source":"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)","metadata":{"trusted":true},"outputs":[],"execution_count":3},{"id":"ce09395e-ecbc-46f4-8f8b-8412070b5299","cell_type":"code","source":"clf = DecisionTreeClassifier(random_state=42)\nclf.fit(X_train, y_train)","metadata":{"trusted":true},"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"DecisionTreeClassifier(random_state=42)","text/html":"<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(random_state=42)</pre></div></div></div></div></div>"},"metadata":{}}],"execution_count":4},{"id":"0de4d0ab-103c-47e4-88dc-a8f4255b75a4","cell_type":"code","source":"y_pred = clf.predict(X_test)","metadata":{"trusted":true},"outputs":[],"execution_count":5},{"id":"38c19142-a05d-4688-a648-d0720e17b17e","cell_type":"code","source":"cm = confusion_matrix(y_test, y_pred)","metadata":{"trusted":true},"outputs":[],"execution_count":6},{"id":"caffe7e2-c9c2-496f-9a37-bb01c4f6ddfc","cell_type":"code","source":"disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=iris.target_names)\ndisp.plot(cmap=plt.cm.Blues)\nplt.title('Confusion Matrix for Decision Tree Classifier')\nplt.show()\n","metadata":{"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 640x480 with 2 Axes>","image/png":"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"},"metadata":{}}],"execution_count":7},{"id":"17c536ed-ef57-40f8-a1fc-df5811ef989e","cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}