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Explore the Extended Definitions, OML Guides, Block Library, API Guide and Glossary.
Reference Guide for OpenMatrix Language Functions
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
Machine Learning Commands
Regression

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Reference Guides
Explore the Extended Definitions, OML Guides, Block Library, API Guide and Glossary.
- Extended Definitions for Advanced Users
  PDF file with in-depth information on key topics in the User's Guide.
- Scripting Guide for OpenMatrix Language
  OpenMatrix is a mathematical scripting language.
- Reference Guide for OpenMatrix Language Functions
  The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
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    - Regression
      - dtrfit
        A decision tree regressor.
      - dtrpredict
        Predicts target values for the test data points using parameters computed by dtrFit function.
      - knnregressorfit
        Trains the K Nearest Neighbors Regressor from the training dataset and computes the required parameters to be used by knnregressorpredict method for making predictions.
      - knnregressorpredict
        Predicts target values for the test data points using parameters computed by knnregressorfit function.
      - lassofit
        Regression estimator. Linear Model trained with L1 regularization technique (Lasso).
      - lassopredict
        Predicts target values for the test data points using parameters computed by lassofit function.
      - linearfit
        Linear Regression. It uses Gradient Descent to estimate the coefficients.
      - linearpredict
        Predicts target values for the test data points using parameters computed by linearfit function.
      - olsfit
        Ordinary Least Squares Linear regression.
      - olspredict
        Predicts target values for the test data points using parameters computed by olsFit function.
      - rfrfit
        A Random Forest regressor. Random Forest is an estimator that fits number of regression decision trees on various sub-samples of the dataset and uses averaging to improve predictive accuracy and control over fitting.
      - rfrpredict
        Predicts target values for the test data points using parameters computed by rfrFit function.
      - ridgefit
        Linear regression with L2 regularization.
      - ridgepredict
        Predicts target values for the test data points using parameters computed by ridgeFit function.
      - svrfit
        Epsilon-Support Vector regression.
      - svrpredict
        Predicts target values for the test data points using parameters computed by svrFit function.
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- Block Reference Guide
  Describes all of the blocks in the installed Twin Activate library.
- Function Guide for Twin Activate
  Provides information about developing and simulating models through the Twin Activate Application Program Interface.
- Glossary
  Key terms associated with the software.
Frequently Asked Questions
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Regression

Attention: Available only with Twin Activate commercial edition.

The mathematical methods for predicting a continuous outcome are:

Linear Regression
KNN Regressor
Decision Tree Regressor
Random Forest Regressor
Ridge Regression
Lasso Regression
Support Vector Regressor