machine learning - Features (Attributes) ranking -


i have dataset items , features (attributes). each item has features.

total number of features ~400 feature.

i want rank features based on importance. not looking classification, looking features ranking.

i convert item-feature binary matrix fowllowing, 1 means feature exists in item , 0 otherwise.

itemid | feature1 | feature2 | feature3 | feature4 .... 1 | 0 | 1 | 1 | 0 2 | 1 | 0 | 0 | 1 3 | 1 | 1 | 1 | 0 4 | 0 | 0 | 1 | 1

an example of real data hotels, features like: air condition, free wifi, etc.

hotelid | air condition| free wifi .... 1 | 0 | 1 2 | 1 | 0 3 | 1 | 1 4 | 0 | 0 .....

i need know use , how use it.

a sample code appreciated

it looks looking algorithm such information gain. taken documentation of class:

evaluates worth of attribute measuring information gain respect class

here can find usage example:

http://www.programcreek.com/java-api-examples/index.php?api=weka.attributeselection.infogainattributeeval

good luck.


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