[B! classification][machine-learning] IanLewisのブックマーク

IanLewis id:IanLewis

classificationとmachine-learningに関するIanLewisのブックマーク (2)

Videolectures
IanLewis 2010/03/15
We introduce confidence-weighted linear classifiers, a new class of algorithms that maintain confidence information about classifier parameters. Learning in this framework updates parameters by estimating weights and increasing model confidence. We investigate a new online algorithm that maintains a

linear-classification

machine-learning

classification

text

text-processing
リンク
Random forest - Wikipedia
Random forests or random decision forests is an ensem ble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time. For classification tasks, the output of the random forest is the class selected by most trees. For regression tasks, the mean or average prediction of the individual trees is returned.[1][2] Random deci
IanLewis 2010/01/21
Random naive Bayes extends the Naive Bayes classifier by adopting the random forest principles: random input selection (bagging, i.e. bootstrap aggregating) and random feature selection ([1]).

machine-learning

bayes

bayesian

random-forest

classification
リンク
1

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