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DataMining

There are two sets of Wikipedia articles. The first set is from Wikipedia featured articles of a

certain type. The first set becomes class Featured. The second set of articles are Wikipedia (non-

featured) articles of similar type to featured articles. The second set becomes class Non-Featured.

We are dealing with a binary classification problem. 

To create attributes, extract all possible tokens from the entire dataset after stemming and stop-

word removal. Create 1-gram, 2-gram and 3-grams from these tokens. Use these n-grams as the

attributes for ARFF files. 

Perform attribute selection on each of 1-gram, 2gram, 3-gram an using information gain and gain

ratio. Perform classification using decision tree, and naïve Bayes. 

Make a Wiki report on your finding including various statistical evaluation measures given by

WEKA for each classifier.

Skills: Python

See more: moset tree saves files, mosets tree xml files, files template micorsoft word

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