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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
Model Selection

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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.
  - ABF Commands
  - Altair Integration Commands
  - Audio Commands
  - CAE Commands
  - CAE Reader Commands
  - CAE Reader 3D Commands
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  - Calculus Commands
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  - Core Minimal Interpreter Commands
  - Data Structure Commands
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  - Elementary Math Commands
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  - hstpyfit Commands
  - Image Commands
  - JSON Commands
  - Library Manager Commands
  - Linear Algebra Commands
  - Logical Commands
  - Machine Learning Commands
    - Apriori
    - Association Rules
    - Classification
    - Clustering
    - Decomposition
    - Distance
    - Evaluation Metrics
    - K-Mode Clustering
    - Model Selection
      - crossvalscore
        For the given estimator and dataset, it automatically applies cross validation and returns the cross validation score and corresponding model parameters.
      - getfold
        Utility function used to retrieve folds in iterations which are returned by splitter functions.
      - kfold
        Provides train and validation indices for cross validation.
      - leaveoneout
        Provides train and validation indices for cross validation. It’s like K Fold where K is set to the total number of records in the dataset. For larger datasets, this is not an efficient one.
      - stratifiedkfold
        Provides train and validation indices for cross validation while preserving the percentage of samples for each class unlike K Fold.
    - Preprocessing
    - Regression
  - Optimization Commands
  - Plotting Commands
  - Polynomial Math Commands
  - Signal Processing Commands
  - Statistical Analysis Commands
  - String Operations Commands
  - System Commands
  - Table Commands
  - Time Commands
  - Trigonometry Commands
  - OML to Python Bridge Commands
  - Python to OML Bridge Commands
- 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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Model Selection

Attention: Available only with Twin Activate commercial edition.

The following commands are available to split train- and test-data. The commands can be applied to avoid overfitting, which is the event that occurs when a model fits exactly against its training data:

Model Validation

Cross Validation Score

Splitter

K Fold
Leave One Out
Stratified K Fold