Regression analysis advanced (analysis)

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