Machine Learning Algorithms for Classification Rob Schapire Princeton University
Machine Learning • studies how to automatically learn to make accurate predictions based on past observations • classification problems: • classify examples into given set of categories new example labeled training examples machine learning algorithm classification rule predicted classification
Examples of Classification Problems • text categorization (e.g., spam filtering) • fraud detection • optical character recognition • machine vision (e.g., face detection) • natural-language processing (e.g., spoken language understanding) • market segmentation (e.g.: predict if customer will respond to promotion) • bioinformatics (e.g., classify proteins according to their function) .. .
Characteristics of Modern Machine Learning • primary goal: highly accurate predictions on test data • goal is not to uncover underlying “truth” • methods should be general purpose, fully automatic and “off-the-shelf” • however, in practice, incorporation of prior, human knowledge is crucial • rich interplay between theory and practice • emphasis on methods that can handle large datasets