Learning classifiers from distributed, semantically heterogeneous, autonomous data sources by - Random naive Bayes - Document - PDFSEARCH.IO

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	Learning classifiers from distributed, semantically heterogeneous, autonomous data sources by Add to Reading List Document Date: 2005-01-08 20:51:16 Open Document File Size: 1,46 MB Share Result on Facebook Company C2 / / Facility Graduate College / / IndustryTerm greedy algorithm / learning algorithm / / Organization Study Committee / Iowa State University / / Person Fernandez-Baca Leslie Miller / David Fernandez-Baca Leslie / Dianne Cook Drena Dobbs David / / Position Major / General / Professor / / ProvinceOrState Iowa / / Technology learning algorithm / 29 2.3 ID3 algorithm / Vector Machines algorithm / 3.3 Perceptron Algorithm / Nearest Neighbors algorithm / Machine Learning / 4.2 Planning Algorithm / 127 4.4 Algorithms / 2.5 The Perceptron algorithm / Perceptron Algorithm / 15 49 The Perceptron algorithm / relational database / 2.16 50 The SVM algorithm / 79 The Perceptron algorithm / 8 2.1 Learning algorithm / 38 2.9 The Dual Perceptron algorithm / 58 3.3 Algorithms / 3.2 Decision Tree Algorithm / 51 k-NN Algorithm / / SocialTag Statistical classification Bayesian statistics Ensemble learning Margin classifier Naive Bayes classifier K-nearest neighbor algorithm Perceptron Weka Random subspace method Statistics

Learning classifiers from distributed, semantically heterogeneous, autonomous data sources byAdd to Reading List