November 2006
Beginner to intermediate
292 pages
7h 26m
English
book
Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
by Glenn J. Myatt
Content preview from Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
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7.9 FURTHER READING
For more information on methods for combining models, such as bagging and boosting, see Witten (2000), and for confidence metrics for simple linear regression see Kachigan (1991), Donnelly (2004), and Levine (2005). Fausett (1994) provides additional details on Neural Networks. The following indicates sources of additional information on the following topics: multiple linear regression (Kleinbaum 1998), logistic regression (Agresti 2002), random forests (Kwok 1990), rule-based classifiers (Tang 2005), Naïve Bayes (Tang 2005), partial least squares regressions (Wold 1975), and support vector machines (Cristianini 2000).
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