Answers for "Use a simple model on data to create a confusion matrix. Compute the accuracy, precision, sensitivity, specificity, F-score, and G-score."

import sklearn.metrics from plot_confusion_matrix

from sklearn.metrics import plot_confusion_matrix

Posted by: Guest on October-17-2020

from sklearn.metrics import confusion_matrix pred = model.predict(X_test) pred = np.argmax(pred,axis = 1) y_true = np.argmax(y_test,axis = 1)

from sklearn.metrics import confusion_matrix
pred = model.predict(X_test)
pred = np.argmax(pred,axis = 1) 
y_true = np.argmax(y_test,axis = 1)

Posted by: Guest on June-14-2020

Code answers related to "Use a simple model on data to create a confusion matrix. Compute the accuracy, precision, sensitivity, specificity, F-score, and G-score."