Titlebook: Applied Machine Learning; David Forsyth Textbook 2019 Springer Nature Switzerland AG 2019 machine learning.naive bayes.nearest neighbor.SV

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書目名稱Applied Machine Learning影響因子(影響力)




書目名稱Applied Machine Learning影響因子(影響力)學科排名




書目名稱Applied Machine Learning網(wǎng)絡公開度




書目名稱Applied Machine Learning網(wǎng)絡公開度學科排名




書目名稱Applied Machine Learning被引頻次




書目名稱Applied Machine Learning被引頻次學科排名




書目名稱Applied Machine Learning年度引用




書目名稱Applied Machine Learning年度引用學科排名




書目名稱Applied Machine Learning讀者反饋




書目名稱Applied Machine Learning讀者反饋學科排名

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感情脆弱

Regression final example, you can think of classification as a special case of regression, where we want to predict either +?1 or ??1; this isn’t usually the best way to proceed, however. Predicting values is very useful, and so there are many examples like this.

前兆

Learning to Classify free on the web, you would use a classifier to decide whether it was safe to run it (i.e., look at the program, and say yes or no according to some rule). As yet another example, credit card companies must decide whether a transaction is good or fraudulent.

吹牛需要藝術(shù)

A Little Learning Theoryis going to behave well on test—we need some reason to be confident that this is the case. It is possible to bound test error from training error. The bounds are all far too loose to have any practical significance, but their presence is reassuring.

預兆好

High Dimensional Datances, rather than correlations, because covariances can be represented in a matrix easily. High dimensional data has some nasty properties (it’s usual to lump these under the name “the curse of dimension”). The data isn’t where you think it is, and this can be a serious nuisance, making it difficult to fit complex probability models.

解決

Clustering Using Probability Models a natural way of obtaining soft clustering weights (which emerge from the probability model). And it provides a framework for our first encounter with an extremely powerful and general algorithm, which you should see as a very aggressive generalization of k-means.

miracle

Regression: Choosing and Managing Modelsus chapter, we saw how to find outlying points and remove them. In Sect. 11.2, I will describe methods to compute a regression that is largely unaffected by outliers. The resulting methods are powerful, but fairly intricate.

幼稚

Textbook 2019 for people who want to adopt and use the main tools of machine learning, but aren’t necessarily going to want to be machine learning researchers. Intended for students in final year undergraduate or first year graduate?computer science programs in machine learning, this textbook is a?machine learni