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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

389 个评分
61 条评论


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....


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.

Nov 6, 2019

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


51 - 数据挖掘中的聚类分析 的 62 个评论(共 62 个)

创建者 Venuu M

Apr 11, 2019

The course helped me a lot. I loved this course

创建者 Yogesh S M

Jan 27, 2017

Learnt More Here Than I Did At My College!!

创建者 Red R

Jan 18, 2022

T​here are still unclear lessons


Feb 21, 2019

Nice. Good Course

创建者 aditya p

Feb 15, 2017

good course!

创建者 prasanna k p

Nov 22, 2019

it will be very helpful for understanding if any examples given with dummy data for cluster evaluation

创建者 Aden G

Oct 15, 2016

I am concerned about the last assignment of this course. And I cannot get any help from here.

创建者 Su-hyun K

Sep 14, 2021

Test is important, but sometimes it's hard to find answer, kind guidance should be provided

创建者 Chow K M

Apr 3, 2021

Okay as an introduction to key concepts. Lack of depth into the specific calculations.

创建者 Alexandre M B

Nov 11, 2017

My analysis is that the assessments do not match the depth of what is explained.

创建者 Logan V

Jun 27, 2020

needs examples


May 19, 2021

If I sealect an option in quiz it says either »√/× but not display correct option