Regression

Categories

• Regression Learner App
  Interactively train, validate, and tune regression models
  
• Linear Regression
  Multiple, stepwise, multivariate regression models, and more
  
• Generalized Linear Models
  Logistic regression, multinomial regression, Poisson regression, and more
  
• Nonlinear Regression
  Nonlinear fixed- and mixed-effects regression models
  
• Support Vector Machine Regression
  Support vector machines for regression models
  
• Gaussian Process Regression
  Gaussian process regression models (kriging)
  
• Regression Trees
  Binary decision trees for regression
  
• Regression Tree Ensembles
  Random forests, boosted and bagged regression trees
  
• Generalized Additive Model
  Interpretable model composed of univariate and bivariate shape functions for regression
  
• Neural Networks
  Neural networks for regression
  
• Incremental Learning
  Fit linear model for regression to streaming data and track its performance
  
• Direct Forecasting
  Perform direct forecasting using regularly sampled time series data
  
• Interpretability
  Train interpretable regression models and interpret complex regression models
  
• Model Building and Assessment
  Synthetic data generation, feature selection, feature engineering, model selection, hyperparameter optimization, cross-validation, residual diagnostics, and plots
  
• Python Model Coexecution
  Load and coexecute Python machine learning models for prediction in Simulink