added and ran hyperparam script for all different classifiers, but couldn't successfully run the feature selection and hyperparam together
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18 changed files with 131 additions and 142 deletions
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@ -100,17 +100,15 @@ qda_bts_dict['bts_jaccard'] = round(jaccard_score(y_bts, test_predict),2)
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qda_bts_dict
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# Create a df from dict with all scores
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pd.DataFrame.from_dict(qda_bts_dict, orient = 'index', columns = 'best_model')
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qda_bts_df = pd.DataFrame.from_dict(qda_bts_dict,orient = 'index')
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qda_bts_df.columns = ['Logistic_Regression']
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qda_bts_df.columns = ['QDA']
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print(qda_bts_df)
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# Create df with best model params
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model_params = pd.Series(['best_model_params', list(gscv_qda_fit_be_mod.items() )])
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model_params_df = model_params.to_frame()
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model_params_df
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model_params_df.columns = ['Logistic_Regression']
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model_params_df.columns = ['QDA']
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model_params_df.columns
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# Combine the df of scores and the best model params
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