Can anyone please tell me is there any option to select significant input features from a set of input variables for ANN model development in WEKA software. Since I have never experienced with this open source tool, I do not know this aspect.
Any suggestion/guidance would be highly appreciated. Thanks in advance for your time and attention.
The Weka Attribute Evaluator tab allows you to run feature extraction techniques. This way you get to choose which evaluator and which selector will run with the right inputs/features for your data set. Since you will be using ANN, you might want to consider Gini Index feature extraction) for small data sets or you may use the Wrapper attribute evaluator or Ranker for larger data sets. If not you could always use Information Gain.
To get started with the Explorer mode GUI (WEKA version 3.6.13) you can choose an attribute filter for your purpose (supervised learning I assume) this way:
Open an ARFF file, then:
Choose>Filters > supervised > attribute > AttributeSelection > Apply
The column number in the 'Current relation' window should now be reduced.
For more detailed information about WEKA feature selection see the links below.
http://machinelearningmastery.com/feature-selection-to-improve-accuracy-and-decrease-training-time/
https://www.youtube.com/watch?v=UOadhDKRbPM
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