Contents
Is the elements of statistical learning a recommended text?
The Elements of Statistical Learning is an influential and widely studied book in the fields of machine learning, statistical inference, and pattern recognition. It is a standard recom- mended textin many graduatecourses onthese topics.
What are the elements of statistical decision theory?
Chapter 2 (Overview of Supervised Learning) Statistical Decision Theory We assume a linear model: that is we assume y = f(x) + ε, where ε is a random variable with mean 0 and variance σ2, and f(x) = xTβ. Our expected predicted error (EPE) under the squared error loss is EPE(β) = Z (y −xTβ)2Pr(dx,dy).
How many people have searched for statistical learning theory?
A search for “statistical learning theory” on Google (as of 1 January 2010) gave over 4 million hits. The possible disadvantage of not being able to use the book’s problems in an academic course is not really such a large one.
Special thanks to (more recent comments are listed first): Benjamin Schulz, Franklin Wang, Hugh Kinnear, Nicola Doninelli, Landon Lehman, Mark-Jan Nederhof for solutions in Chapter 5. Dan Wang for his bug report in the AdaBoost code, Liuzhou Zhuo for his comments on Exercise 3.25 and Ruchi Dhiman for his comments on Chapter 4.
From the perspective of statistical learning theory, supervised learning is best understood. Supervised learning involves learning from a training set of data. Every point in the training is an input-output pair, where the input maps to an output.
What are the applications of statistical learning theory?
Statistical learning theory deals with the problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as computer vision, speech recognition, bioinformatics and baseball.
Machine learning and. data mining. Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory deals with the problem of finding a predictive function based on data.