11_Optimization
This directory contains 10 workflows.
01_Cross_Validation_with_SVM
A Cross-Validation setup is provided by using a Support-Vector-Machine (SVM) as base learning algorithm.
02_Optimizing_Subset_Selection
This workflow demonstrates multiobjective subset selection using a genetic algorithm. It reads a (artifical) dataset with coordinates and scores for each […]
03_Parameter_Optimization
This workflow demonstrates the usage of the parameter optimization loop nodes. Two optimization strategies can be specified, exhaustive search or hillclimbing.
04_Meassuring_Variable_Importance
This workflow calculates how important each variable is for a correct classification.
05_Score_Erosion_for_Multi_Objective_Optimization
This workflow selects subsets of 100 molecules that are both highly active and diverse at the same time.
06_Parameter_Optimization_two_examples
This workflow shows 2 examples of parameter optimization in a decision tree and in a logistic regression. In the decision tree we optimize the minimum […]
07_Cross_Validation_with_SVM_and_Parameter_Optimization
A Cross-Validation setup is provided by using a Support-Vector-Machine (SVM) as base learning algorithm.
08_Model_Optimization_and_Selection
This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the choice of features and one […]
09_General_Parameter_Optimization_Example
This workflow is an example of how to use the Parameter Optimization component. It optimizes the parameter of the adult dataset.
09_Parameter_Optimization_Example
This workflow is an example of how to use the Parameter Optimization component. It optimizes the parameter of the adult dataset.