Machine Learning User Guide

• Feature Generation
• Feature Selection
  • Feature Selection Processors in Fire Insights
  • VectorSlicer
  • RFormula
  • ChiSqSelector
• Clustering
  • Clustering Processors in Fire Insights
  • Clustering Algorithms in Apache Spark
• Regression
  • Apache Spark
  • Scikit Learn
• Classification
  • Apache Spark MLlib
  • Scikit Learn
  • Classification Algorithms in Scikit Learn
• Prediction
  • What is Prediction?
  • Why are Predictions Important?
  • Predictor => Predicted
  • Usual Examples
  • Techniques
• Model Evaluation
  • Evaluation Processors in Fire Insights
  • Model Evaluation Techniques
  • Holdout
  • Cross-Validation
  • Model Evaluation in Fire Insights
• Model Persistence
  • Persisting SparkML Models
  • Persisting H2O Models
  • Persisting Scikit Learn Models
• Model Serving
  • Scoring with Workflows
  • Serving Spark MLlib Models
  • Serving H2O Models
  • Serving AWS SageMaker models
  • Serving Scikit Learn Models
  • Serving Tensorflow Models
  • Integration with MLflow