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experiment-playing-time

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Optimize playing-time projections through automated feature experiments.

Data & Analytics#machine learning#feature engineering#forecasting#experimentation#playing time
Authoredpaget
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the challenge of improving playing-time projections for batters and pitchers by conducting automated feature experiments.

Core Features & Use Cases

  • Feature Engineering Automation: Run an automated loop to discover and test features that improve the playing-time model.
  • Customizable Experimentation: Allow users to specify the player type and an optional budget for the number of experiments.
  • Model Analysis and Reporting: Diagnose weaknesses in the model, generate and test hypotheses, log results, and present a summary report at the end.

Quick Start

Run the playing-time experiment skill with the batter player type and a budget of 15 iterations:

experiment-playing-time batter --budget 15

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: experiment-playing-time
Download link: https://github.com/edpaget/bot-showalter/archive/main.zip#experiment-playing-time

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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