Confusion matrix interpretation

You are given the actual diagnoses and predicted diagnoses for the heart_disease dataset - actuals and predictions respectively. Import and create a confusion matrix of these diagnoses using the imported confusion_matrix() function in order to select the correct answer. Note that the sklearn output format for confusion matricies is:

	Actual: Heart disease	Actual: No heart disease
Predicted: Heart disease
Predicted: No heart disease

⚠️ Note: Type your code in the IPython Shell terminal and press Enter.

Possible answers

The number of True Positives (TP) is 10

The number of False Positives (FP) is 20

The number of False Negatives (FN) is 50

The number of True Negatives (TN) is 30

Exercise

Confusion matrix interpretation

Instructions

Possible answers

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Instructions

Possible answers

Exercise