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.