formation
发表于 2025-3-21 16:19:35
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heterodox
发表于 2025-3-21 20:28:48
Hang LiProvides introduction to principle machine learning methods, covering both supervised and unsupervised learning methods.Presents clear descriptions, detailed proofs, and concrete examples using concis
Diaphragm
发表于 2025-3-22 02:47:55
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guzzle
发表于 2025-3-22 08:38:57
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敏捷
发表于 2025-3-22 10:39:54
Perceptron,This chapter first introduces the perceptron model, then describes the learning strategy of the perceptron, especially the loss function, and finally presents perceptron learning algorithms, including the primitive form and the dual form, and proves the algorithm’s convergence.
GONG
发表于 2025-3-22 16:08:52
-Nearest Neighbor,This chapter first describes the .-NN algorithm, then discusses the model and three basic elements of .-NN, and finally describes an implementation method of .-NN—the .-tree, focusing on algorithms for constructing and searching the .-tree.
epinephrine
发表于 2025-3-22 18:57:28
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ESPY
发表于 2025-3-22 22:21:57
Decision Tree,This chapter first introduces the basic concept of the decision tree, then introduces feature selection, tree-generation and tree-pruning through ID3 and C4.5 algorithms, and finally introduces the CART algorithm.
Inveterate
发表于 2025-3-23 02:02:09
Logistic Regression and Maximum Entropy Model,This chapter first introduces the logistic regression model, then the maximum entropy model, and finally describes the learning algorithms for logistic regression and maximum entropy models, including the improved iterative scaling algorithm and the Quasi-Newton method.
CRASS
发表于 2025-3-23 06:00:44
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