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学生对 University of Illinois Urbana-Champaign 提供的 Cluster Analysis in Data Mining 的评价和反馈

4.5
408 个评分

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....

热门审阅

DD

Sep 24, 2017

A very good course, it gives me a general idea of how clustering algorithm work.

RG

Jan 24, 2021

The material is too general, does not provide examples. So it's difficult when doing the exam.

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51 - Cluster Analysis in Data Mining 的 63 个评论(共 63 个)

创建者 shane

Sep 6, 2017

Very detailed introduction of Clustering techniques.

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

There are still unclear lessons

创建者 PABLO P Q

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 13, 2021

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

创建者 Chow K M

Apr 2, 2021

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

创建者 Alexandre 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

创建者 MOGARAMPALLI S

May 19, 2021

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