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学生对 伊利诺伊大学香槟分校 提供的 数据挖掘中的聚类分析 的评价和反馈

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课程概述

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications....

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ES

Dec 17, 2018

This was my favorite course in the whole specialization. Everything is explained very concisely and clearly making the subject matter very easy to understand.

VB

Nov 6, 2019

Good course for understanding the Cluster Analysis & Algorithms, instructor is very experienced and well explained, thanks

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1 - 数据挖掘中的聚类分析 的 25 个评论(共 62 个)

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