Takes a list of trained machine learning models and returns diagnostics as a data frame as to compare the effectiveness of algorithms. Measures include Accuracy, Prevalence, Detection Rate, F1, Cohen's Kappa, McNemar P-Value, Negative and Positive Predictive value, Precision, Recall, Sensitivity, and Specificity
make_table(x, test_x, test_y)
A list of models
portion of data you are using to test your predictions.
the true values which you are comparing to your predicted values.
This function returns a
data.frame including columns:
Accuracy P value
McNemar P Value
Negagive Prediction Value
Positive Predictive Value
Method; the algorithm used to train each particular model
"Chad Schaeffer <[email protected]>
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