Cherrypick - ML model Orchestration

Cherrypick is an automated machine learning (Automated-ML) library that simplifies:

• Data preprocessing

• Model selection

• Outlier removal

• Explainability

It helps you quickly train, evaluate, and interpret models with minimal effort.

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Quick Example

from cherrypick import Orchestrator

# For Regression:
cherry = Orchestrator(
                    problem_Statement = 'regression',
                    train = train_reg,
                    test = test_reg,
                    focus_regressor = 'mse',
                    file_dir = 'model_'
                    )
# Orchestrates the model selection
cherry.orchestrate()

# For Classification
  cherry = Orchestrator(
                      problem_Statement = 'classification',
                      train = train_classify,
                      test = test_classify,
                      focus_classifier = 'f1score',
                      file_dir = 'model_'
                    )
# Orchestrates the model selection
cherry.orchestrate()

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Key Features

• Automated model selection

• Built-in explainability (SHAP)

• Performance evaluation tools

• Data preprocessing pipeline

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Installation

Install via pip:

pip install cherrypick-ml

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Contents:

• cherrypick
  • Cherrypick Package