EvalML
v0.5.2

Getting Started

  • What is EvalML
  • Install

Objective functions

  • Overview
  • Fraud Prediction
  • Defining Custom Objectives

Automated Machine Learning

  • Setting up pipeline search
  • Exploring search results
  • Avoiding Overfitting
  • Regression Example

Resources

  • Changelog
  • Roadmap
  • API Reference
EvalML
  • Docs »
  • Overview: module code

All modules for which code is available

  • evalml.demos.breast_cancer
  • evalml.demos.diabetes
  • evalml.demos.fraud
  • evalml.demos.wine
  • evalml.guardrails.utils
  • evalml.models.auto_classifier
  • evalml.models.auto_regressor
  • evalml.objectives.fraud_cost
  • evalml.objectives.lead_scoring
  • evalml.objectives.standard_metrics
  • evalml.pipelines.classification.logistic_regression
  • evalml.pipelines.classification.random_forest
  • evalml.pipelines.classification.xgboost
  • evalml.pipelines.regression.random_forest
  • evalml.pipelines.utils
  • evalml.preprocessing.utils
  • evalml.problem_types.problem_types
  • evalml.problem_types.utils
  • evalml.tuners.skopt_tuner

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