Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

Overview

Clustering

Clustering Application in Python Using scikit-learn

This repository contains the prediction of baseball metric clusters using MLB Statcast Metrics.

ap_mlb_1_stadium

Goals

  • Using MLB Statcast Metrics, summarize and examine baseball statistics.
  • Build a k-Means Clustering model to predict clusters using exit velocity and launch angle as features.
    • Determine the optimal number of clusters using the elbow method and silhouette coefficients.
  • Build a Hierarchical (Agglomerative) Clustering model to predict clusters using exit velocity and launch angle as features.
Owner
Tom Weichle
Data Scientist w/10 years successfully finding meaningful insights in large-scale databases
Tom Weichle
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