introduction整理ppt.ppt

General Information Textbook Grading Homework Dates to Remember How to Succeed in Class What is Machine Learning? Field of Study Multidisciplinary Field What is Machine Learning? Definition Class of Tasks Class of Tasks Settings for learning Experience and Performance Experience and Performance What is Machine Learning? Designing a Learning System Designing a Learning System The Knowledge To Learn The Representation of the Target Knowledge The Representation of the Target Knowledge The Learning Mechanism 1 The Learning Mechanism 2 What is Machine Learning? Application 1 Application 1 Application 2 Application 2 Other Applications What is Machine Learning? Should I care about Machine Learning at all? Summary WEKA Classification Algorithms WEKA Regression Algorithms and Meta-Schemes WEKA weather.arff WEKA attribute declarations Where does machine learning fit in computer science? What is machine learning? Where can machine learning be applied? Should I care about machine learning at all? Yes, you should! Machine learning is becoming increasingly popular and has become a cornerstone in many industrial applications. Machine learning provides algorithms for data mining, where the goal is to extract useful pieces of information (i.e., patterns) from large databases. The computer industry is heading towards systems that will be able to adapt and heal themselves automatically. The electronic game industry is now focusing on games where characters adapt and learn through time. NASA is interested in robots able to adapt to any environment automatically. Machine learning is the study of how to make computers learn. A learning algorithm needs the following elements: class of tasks, performance metric, and body of experience. The design of a learning algorithm requires to define the knowledge to learn, the representation of the target knowledge, and the learning mechanism. Machine learning counts with many successful applications and is becoming increasingly important in