Delta TFIDF: an Improved Feature Space for Text Analysis

Abstract

Bag of words text classification techniques represent documents as a collection of words with associated counts. Machine learning algorithms, such as support vector machines, use these feature spaces to classify new documents using their similarity to a set of manually labeled documents. We describe an efficient way to weight these feature scores to improve classification accuracy