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Learner Reviews & Feedback for Cluster Analysis in Data Mining by University of Illinois Urbana-Champaign

4.5
stars
408 ratings

About the Course

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....

Top reviews

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 - 63 of 63 Reviews for Cluster Analysis in Data Mining

By shane

Sep 7, 2017

Very detailed introduction of Clustering techniques.

By Venuu M

Apr 11, 2019

The course helped me a lot. I loved this course

By Yogesh S M

Jan 27, 2017

Learnt More Here Than I Did At My College!!

By Red R

Jan 18, 2022

There are still unclear lessons

By PABLO P Q

Feb 21, 2019

Nice. Good Course

By aditya p

Feb 15, 2017

good course!

By prasanna k p

Nov 22, 2019

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

By Aden G

Oct 15, 2016

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

By Su-hyun K

Sep 14, 2021

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

By Chow K M

Apr 3, 2021

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

By Alexandre B

Nov 11, 2017

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

By Logan V

Jun 27, 2020

needs examples

By MOGARAMPALLI S

May 19, 2021

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