Examples

• Basic Usages
  • Create and Run an Experiment
  • Set the Number of Search Trials
  • Use Cross Validation
  • Evaluation dataset
  • Set the Evaluation Criterion
  • Set the Early Stopping
  • Choose a Searcher
  • Enable TrialStore
  • Ensemble Models
  • Set Parallelism
  • Set Log Levels
  • Experiment Visualization
• Advanced Usages
  • Data Adaption
  • Data cleaning
  • Feature generation
  • Collinearity detection
  • Drift detection
  • Feature selection
  • UnderSampling pre-search
  • The second stage feature selection
  • Pseudo label
• Handling Imbalanced Data
  • Adopt ClassWeight
  • UnderSampling and OverSampling
• Defining SearchSpace
  • Define Search Space
  • Support Machine Learning Models
• GPU acceleration
  • Accelerate the experiment
  • Customize Search Space
• Distributed training
  • Quick Experiment
  • Define Search Space
• Multi-objectives optimization
  • NSGA-II
  • R-NSGA-II
  • MOEA/D
  • Builtin objectives