![roc curve in spss 20 roc curve in spss 20](https://download.cahdroid.com/wp-content/uploads/2020/12/Download-IBM-SPSS-Statistics-20-Full-Version-2.png)
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Roc curve in spss 20 code#
Use the following code to export the figure. predict_proba ( X_test ) fpr, tpr, _ = roc_curve ( y_test, yproba ) auc = roc_auc_score ( y_test, yproba ) result_table = result_table. fit ( X_train, y_train ) yproba = model. DataFrame ( columns = ) # Train the models and record the resultsįor cls in classifiers : model = cls. # Import the classifiersįrom sklearn.linear_model import LogisticRegression from sklearn.naive_bayes import GaussianNB from sklearn.neighbors import KNeighborsClassifier from ee import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier from trics import roc_curve, roc_auc_score # Instantiate the classfiers and make a listĬlassifiers = # Define a result table as a DataFrame
![roc curve in spss 20 roc curve in spss 20](https://graphpad.ir/wp-content/uploads/2018/07/roc-curve-1-graphpad.ir_-800x696.png)
Here, we’ll train the models on the training set and predict the probabilities on the test set.Īfter predicting the probabilities, we’ll calculate the False positive rates, True positive rate, and AUC scores.