Comparing Outlier Detection Methods

Using batting stats from Major League Baseball’s 2023 season

Outlier detection is an unsupervised machine learning task to identify anomalies (unusual observations) within a given data set. This task is helpful in many real-world cases where our available dataset is already “contaminated” by anomalies. Scikit-learn implements several outlier detection algorithms, and in cases where we have an uncontaminated baseline, we can also use these algorithms for novelty …

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