百科全书
发表于 2025-3-23 12:17:02
Hidden Markov Model,This chapter first introduces the basic concepts of the Hidden Markov Model, and then describes the probability calculation algorithms, learning algorithms, and prediction algorithms of the HMM, respectively.
预定
发表于 2025-3-23 17:42:40
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Jogging
发表于 2025-3-23 19:12:56
Summary of Supervised Learning Methods,This chapter summarizes the characteristics of ten supervised learning methods, including the perceptron, .-Nearest-Neighbor (.-NN), the Naïve Bayes method, the decision tree, logistic regression and maximum entropy model, Support Vector Machine (SVM), Boosting, the EM algorithm, Hidden Markov Model (HMM), and Conditional random field (CRF).
变白
发表于 2025-3-24 01:26:33
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mitten
发表于 2025-3-24 04:13:03
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thyroid-hormone
发表于 2025-3-24 09:13:56
Singular Value Decomposition,This chapter introduces the matrix factorization method—Singular Value Decomposition (SVD), including the definition and fundamental theorem of matrix SVD, its compact and truncated form, geometric interpretation, and main properties, its optimization algorithms.
SHRIK
发表于 2025-3-24 12:40:21
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Evolve
发表于 2025-3-24 15:08:25
Latent Semantic Analysis,This chapter introduces an unsupervised learning method—Latent Semantic Analysis (LSA), first describing the word vector space model and the topic vector space model, followed by the SVD algorithm for LSA, and the Non-negative matrix factorization (NMF) algorithm.
流动性
发表于 2025-3-24 20:14:19
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erythema
发表于 2025-3-25 01:04:53
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