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qinhanmin2014's
repositories
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02 Classifying with k-Nearest Neighbors
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03 Splitting datasets one feature at a time decision trees
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04 Classifying with probability theory naive Bayes
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05 Logistic regression
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06 Support vector machines
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07 Improving classification with the AdaBoost meta-algorithm
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08 Predicting numeric values regression
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09 Tree-based regression
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10 Grouping unlabeled items using k-means clustering
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11 Association analysis with the Apriori algorithm
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12 Efficiently finding frequent itemsets with FP-growth
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13 Using principal component analysis to simplify data
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14 Simplifying data with the singular value decomposition
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15 Big data and MapReduce
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Errata for Machine Learning in Action.pdf
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MLiA_SourceCode.zip
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Machine Learning in Action (Chinese version).pdf
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Machine Learning in Action (English version).pdf
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README.md
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