Skip to content

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

Notifications You must be signed in to change notification settings

tweichle/Clustering

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 

Repository files navigation

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.