Nevertheless you can of course start with reducing to 30 variables maybe due to time issues. I am trying to use ant search with default evaluator fuzzy rough subset and CfsSubsetEval for attribute evaluator. Sorry, I do not have a worked example of GAs for feature selection. I am a bit new in Data Mining. I just now want if these results are satisfactory to adaopt this solution. Evaluate the attribute sets and select only the best k. Sorry, I do not have an example.
RapidMiner provides you with some great out-of-the-box tools for feature selection, for example weighting algorithm operators such as Weight.
Comparison of Feature Selection Strategies for Classification using Rapid Miner. Feature selection is observed to be an lively and vigorous research area in many fields  ABSTRACT: Feature selection is an important part in any of the data KEYWORDS: Feature selection, Optimized selection, Genetic algorithm, Rapid miner.
The 14th attribute representing the class is nominal and consiists of 12 actions that can be performed by the systems.
It seems that Weka has really helped you in your machine learning journey. Perhaps you could use a smaller sample of your data for feature selection?
Feature Selection Part 2 Using the Feature Selection Extension — RapidMiner Community
This input port expects an ExampleSet. January edited December in Knowledge Base. When performing feature selection, should we perform it in the entire dataset training and testing and then split the data?
But another way to use wrapperbased feature selection methods cheaply is to use RapidMiner, a GNU.
How to Perform Feature Selection With Machine Learning Data in Weka
How feature selection is supported on the Weka platform. How to use various different feature selection techniques in Weka on your dataset. Let's get started . (information_theory). Reply.
Shailesh November 4, at am. By the way, the feature selection itself should also be validated, at least by a hold-out set.
Feature Selection to Improve Accuracy and Decrease Training Time
Figure 2: RapidMiner process to evaluate the stability and performance of the MRMR feature selection algorithm in dependency of the number of selected features.
I remove these attribute. The Attribute Evaluator is the method by which a subset of attributes are assessed. Thierry Bachmann January 24, at am.