{"cells": [{"cell_type": "markdown", "metadata": {"papermill": {"exception": false, "start_time": "2020-10-29T02:55:17.965809", "end_time": "2020-10-29T02:55:17.986798", "duration": 0.020989, "status": "completed"}, "tags": []}, "source": "# Feature Importance"}, {"cell_type": "code", "execution_count": 1, "metadata": {"execution": {"iopub.execute_input": "2020-10-29T02:55:18.013832Z", "iopub.status.busy": "2020-10-29T02:55:18.012801Z", "iopub.status.idle": "2020-10-29T02:55:20.411850Z", "shell.execute_reply": "2020-10-29T02:55:20.409832Z"}, "papermill": {"exception": false, "start_time": "2020-10-29T02:55:17.996799", "end_time": "2020-10-29T02:55:20.411850", "duration": 2.415051, "status": "completed"}, "tags": []}, "outputs": [], "source": "import pandas as pd\nimport data_describe as dd\n\nfrom sklearn.naive_bayes import GaussianNB"}, {"cell_type": "code", "execution_count": 2, "metadata": {"execution": {"iopub.execute_input": "2020-10-29T02:55:20.436830Z", "iopub.status.busy": "2020-10-29T02:55:20.435831Z", "iopub.status.idle": "2020-10-29T02:55:20.438798Z", "shell.execute_reply": "2020-10-29T02:55:20.439831Z"}, "papermill": {"exception": false, "start_time": "2020-10-29T02:55:20.420830", "end_time": "2020-10-29T02:55:20.439831", "duration": 0.019001, "status": "completed"}, "tags": []}, "outputs": [], "source": "import warnings\nwarnings.simplefilter(\"ignore\")"}, {"cell_type": "code", "execution_count": 3, "metadata": {"execution": {"iopub.execute_input": "2020-10-29T02:55:20.463831Z", "iopub.status.busy": "2020-10-29T02:55:20.462830Z", "iopub.status.idle": "2020-10-29T02:55:20.566830Z", "shell.execute_reply": "2020-10-29T02:55:20.565798Z"}, "papermill": {"exception": false, "start_time": "2020-10-29T02:55:20.448832", "end_time": "2020-10-29T02:55:20.566830", "duration": 0.117998, "status": "completed"}, "tags": []}, "outputs": [{"output_type": "execute_result", "metadata": {}, "data": {"text/plain": " mean radius mean texture mean perimeter mean area mean smoothness \\\n0 17.99 10.38 122.8 1001.0 0.1184 \n\n mean compactness mean concavity mean concave points mean symmetry \\\n0 0.2776 0.3001 0.1471 0.2419 \n\n mean fractal dimension ... worst texture worst perimeter worst area \\\n0 0.07871 ... 17.33 184.6 2019.0 \n\n worst smoothness worst compactness worst concavity worst concave points \\\n0 0.1622 0.6656 0.7119 0.2654 \n\n worst symmetry worst fractal dimension target \n0 0.4601 0.1189 0 \n\n[1 rows x 31 columns]", "text/html": "
\n | mean radius | \nmean texture | \nmean perimeter | \nmean area | \nmean smoothness | \nmean compactness | \nmean concavity | \nmean concave points | \nmean symmetry | \nmean fractal dimension | \n... | \nworst texture | \nworst perimeter | \nworst area | \nworst smoothness | \nworst compactness | \nworst concavity | \nworst concave points | \nworst symmetry | \nworst fractal dimension | \ntarget | \n
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n17.99 | \n10.38 | \n122.8 | \n1001.0 | \n0.1184 | \n0.2776 | \n0.3001 | \n0.1471 | \n0.2419 | \n0.07871 | \n... | \n17.33 | \n184.6 | \n2019.0 | \n0.1622 | \n0.6656 | \n0.7119 | \n0.2654 | \n0.4601 | \n0.1189 | \n0 | \n
1 rows \u00d7 31 columns
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