Precision Metric
Core Metrics DS practice problem on Onlearn.
Difficulty: easy.
Topics: Precision Metric, False Positive Rate, Positive Predictive Value, Precision-Recall Tradeoff, Type I Error, Decision Boundary Sensitivity, Model Evaluation & Selection, Statistical Inference, Information Theory, Supervised Learning, Decision Theory, Classification Performance Metrics, Confusion Matrix Analysis, Probabilistic Modeling, Binary Classifier Thresholding, Error Analysis Frameworks.
Write a Python function precision that calculates the precision metric given two numpy arrays: y true and y pred. The y true array contains the true binary labels, and the y pred array contains the predicted binary labels. Precision is defined as the ratio of true positives to the sum of true positives and false positives.