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Exercise

Compute confusion matrix

As you learned in the video the logistic regression model generates two types of predictions, a continuous valued prediction, in the form of a probability, and a class prediction which in the example of the wells dataset is a discrete category with two classes.

In the previous exercise you computed the continuous values prediction in the form of a probability. In this exercise you will use those values to assign a class to each observation in your wells_test sample. Finally you will describe the model using the confusion matrix.

Computed predictions prediction and wells_test are loaded in your workspace.

Instructions 1/3

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  • Using computed predictions prediction, classify them into 0 and 1 class labels by using the cutoff set at 0.5 and save as y_prediction.