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Working on the Kaggle StumbleUpon evergreen classification challenge: http://www.kaggle.com/c/stumbleupon 1. Apply SVM using pre-existing features supplied. (Put all data points into a vector space, draw a best-fit plane separating the datapoints of each classification.) Probably not going to give good results here but a good exercise. 2. Principal component discriminant analysis: See if a single feature dominates the result. (Oscar says this is isomorphic to LU decomposition - need to look at an example of this.) 3. Extract additional features from the raw text. Word frequency - see if there are words which are indicators of evergreen-ness. 4. Pull apart the url. Definitely domain and non-domain. 5. CART: An algorithm for building binary classification trees.
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Kaggle project for StumbleUpon evergreen-ness classification
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