Difference between revisions of "Regression analysis advanced (analysis)"
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Revision as of 16:33, 12 March 2019
- Analysis title
- Regression analysis advanced
- Provider
- Institute of Systems Biology
- Class
RegressionAnalysisAdvanced
- Plugin
- biouml.plugins.machinelearning (Machine learning)
Description
Create and save regression model or load regression model for prediction of response or cross-validation of regression model.
Parameters:
- Regression mode – Select regression mode
- Regression type – Select regression type
- Path to data matrix – Path to table or file with data matrix
- Variable names – Select variable names
- Response name – Select response name
- Path to folder with saved model – Path to folder with saved model
- Percentage of data for training – Proportion (in %) of data for training
- Parameters for OLS-regression – Please, determine parameters for Odinary least squares regression
- Max number of rotations – Maximal number of rotations for calculation of inverse matrix or eigen vectors
- Epsilon for rotations – Epsilon for calculation of inverse matrix or eigen vectors
- Parameters for WLS-regression – Please, determine parameters for Weighted least squares regression
- Max number of rotations – Maximal number of rotations for calculation of inverse matrix or eigen vectors
- Epsilon for rotations – Epsilon for calculation of inverse matrix or eigen vectors
- Parameters for PC-regression – Please, determine parameters for Principal component regression
- Max number of rotations – Maximal number of rotations for calculation of inverse matrix or eigen vectors
- Epsilon for rotations – Epsilon for calculation of inverse matrix or eigen vectors
- Number of principal components – Number of principal components
- Principal component sorting type – Sorting type of principal components
- Parameters for Tree-based regression – Parameters for Tree-based regression
- Minimal node size – Minimal size of node
- minimal variance – minimal variance
- Path to output folder – Path to output folder