Intuitive
发表于 2025-3-23 11:47:48
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微尘
发表于 2025-3-23 17:20:07
Numerical Vectors the summarization on this chapter and the further discussions. This chapter is intended to characterize mathematically vectors and matrices as the foundation for understanding machine learning algorithms.
upstart
发表于 2025-3-23 18:28:46
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评论者
发表于 2025-3-23 23:21:13
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闲荡
发表于 2025-3-24 03:09:43
Instance Based LearningNN. We also present the modified versions of KNN as its variants. In this chapter, we assume that the KNN is the supervised learning algorithm, but we cover its unsupervised version in the next part..In Sect. 5.1, we provide the overview of the instance based learning, and in Sect. 5.2, we mention t
航海太平洋
发表于 2025-3-24 07:25:50
Probabilistic Learningo provide the background for understanding the chapter. We describe in detail some probabilistic classifiers such as Bayes Classifier and Naive Bayes as the popular and simple machine learning algorithms. We cover the Bayesian Learning as the more advanced learning methods than the two probabilistic
神经
发表于 2025-3-24 14:26:03
Decision Treemples, entirely. In Sect. 7.4, we mention some variants of the decision tree, and in Sect. 7.5, we make the summarization on this chapter and the further discussions. This chapter is intended to describe the classification process, the learning process, and the variants of the decision tree.
TIGER
发表于 2025-3-24 15:57:20
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小隔间
发表于 2025-3-24 19:51:06
K Means Algorithme k means algorithm. In Sect. 10.4, we mention the variants of the k means algorithm, and in Sect. 10.5, we make the summarization on this chapter and the further discussions. This chapter is intended to describe the clustering process and the variants of the k means algorithm.
tendinitis
发表于 2025-3-25 00:59:18
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