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Machine Learning & Data Mining What is Machine Learning? a branch of artificial intelligence, concerns the construction and study of systems that can learn from data. The core of machine learning deals with representation and generalization: Representation of data instances and functions evaluated on these instances are part of all machine learning systems. Generalization is the property that the system will perform well on unseen data instances Tom M. Mitchell: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E” From Wikipedia (Machine Learning) 2 Machine Learning Types Supervised learning Classification Regression/Prediction Unsupervised learning Clustering Semi-supervised learning Association Analysis Reinforcement learning Growth of Machine Learning Machine learning is preferred approach to Speech recognition, Natural language processing Computer vision Medical outcomes analysis Robot control Computational biology This trend is accelerating Improved machine learning algorithms Improved data capture, networking, faster computers Software too complex to write by hand New sensors / IO devices Demand for self-customization to user, environment It turns out to be difficult to extract knowledge from human experts→failure of expert systems in the 1980’s. 4 Data Mining/KDD Definition := “KDD is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” (Fayyad) Applications: Retail: Market basket analysis, Customer relationship management (CRM) Finance: Credit scoring, fraud detection Manufacturing: Optimization, troubleshooting Medicine: Medical diagnosis Telecommunications: Quality of service optimization Bioinformatics: Motifs, alignment ... 5 Machine Learning & Data Mining Machine lea

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