AI/ML a good method for printing model performance info

 

# Creating a common fun  0-0OOction which is usable to print the accuracy metrics of different models

def evaluate_performance(actual, pred):

    # Accuracy Score

    acc_score = round(accuracy_score(actual, pred)*100,2)

    

    # Confusion matrix

    confusion = confusion_matrix(actual, pred)

   

    TP = confusion[1,1] # true positive 

    TN = confusion[0,0] # true negatives

    FP = confusion[0,1] # false positives

    FN = confusion[1,0] # false negatives

    

    # Calculating Sensitivity/Recall

    sensitivity_recall = (TP / float(TP + FN))

    sensitivity_recall = round(sensitivity_recall,2)

  

    # Calculating Specificity

    specificity = (TN / float(TN + FP))

    specificity = round(specificity,2)  

  

    # Calculating Precision

    precision = (TN / float(TN + FP))

    precision = round(precision,2)  

    

    # Calculating F_1 score

    f1_score = 2 * ((precision * sensitivity_recall) / (precision + sensitivity_recall))

    f1_score = round(f1_score,2)  

    

    return pd.DataFrame([{"TP":TP,"TN":TN,"FP":FP,"FN":FN,"Recall":sensitivity_recall,"Precision":precision,"Specificity":specificity,"F1-Score":f1_score,"Accuracy":acc_score}])