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일리노이대학교 어버너-섐페인캠퍼스의 Cluster Analysis in Data Mining 학습자 리뷰 및 피드백

4.5
별점
393개의 평가
62개의 리뷰

강좌 소개

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....

최상위 리뷰

ES

2018년 12월 17일

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

2019년 11월 6일

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

필터링 기준:

Cluster Analysis in Data Mining의 62개 리뷰 중 26~50

교육 기관: Dr. P N

2020년 10월 14일

A wonderful learning experience !

교육 기관: Pavan G

2017년 10월 2일

Explained with nice examples

교육 기관: Leela P

2017년 1월 16일

Very useful and well taught

교육 기관: AJETUNMOBI O

2017년 5월 1일

Clustering demytified

교육 기관: Ankit

2020년 2월 12일

Fantastic course

교육 기관: Christopher D

2016년 11월 8일

Great course!

교육 기관: VIDUSHI M

2019년 3월 17일

Excellent!

교육 기관: KRUPAL J K

2019년 4월 9일

VERY GOOD

교육 기관: Oren

2017년 6월 7일

Very good

교육 기관: Hernan C V

2017년 7월 1일

Awesome!

교육 기관: vaseem a

2019년 4월 8일

awesome

교육 기관: Alan J R

2020년 2월 20일

great!

교육 기관: Valerie P

2017년 7월 11일

E

교육 기관: geoffrey a

2017년 9월 2일

Good, thorough coverage -- for a 4-week course -- of how to cluster. I liked the evaluation of clustering topic especially. Very few other instructors seem to discuss the vitally important evaluation of clustering results in any depth when they teach clustering. Dr. Han explained a comprehensive framework for understanding the effectiveness of any clustering system. I had never seen some of this material before, even though clustering was a topic appearing in a couple of other data science or machine learning courses that I have taken in the past. Ideally I would even wish to see this course extended to 6 or 8 weeks, so that case studies on difficult real datasets can be clustered. For example I had a terribly difficult ordeal last year before I took this course, trying to cluster the Kaggle.com dataset of the BOSCH competition. It has about 90% missing data in every row, and there are 2 million rows in total, and about 4500 columns! Kaggle's BOSCH is a SUPER tough dataset to work with! I hope to come back to try the BOSCH dataset again using my new knowledge of clustering some time soon. The reason I chose to run unsupervised clustering on this BOSCH dataset, which is ostensibly intended for supervised learning, is to eliminate significant amounts of the missing data from being exposed to multiple individual supervised learning models by prior clever grouping of examples. I am still postulating to the current day that clustering and creating another unique supervised learning model for each cluster is the most important step to eliminating missing data in this particular problem.

교육 기관: David M

2020년 6월 12일

Enjoyed the course. Though there is no programming content, the assignments require such. So, participants should have some prerequisite skills in either R, Phyton or other statistical software to perform. What I like is that the contents cover the "maths" of cluster analysis, though not very deep.

교육 기관: Cassius d O P

2021년 4월 17일

It was definitely an instructive course. I liked a lot the insights and discussion about different clustering methods and algorithms. The downside of this course is the scanty discussion about the practical implementation/usage of these algorithms.

교육 기관: GANG L

2018년 1월 26일

This is a very good course covering all area of clustering. The only thing I feel a little struggle is some algorithm explained too brief, I prefer some detail step by step examples.

교육 기관: Devender B

2019년 3월 10일

Useful theory. It will be challenging for non-math students. and also lecturer's native language influence iis going to be challening as well to follow along.

교육 기관: Umesh G

2019년 4월 28일

Its Good but explanations can done much better, rest all good in terms of study material, quiz ,and programming assignment.

교육 기관: Haf M

2021년 7월 22일

The course is good. learned alot but videos are boring and hard to understand due to more and more text on slides

교육 기관: Alexander S

2019년 12월 16일

Good course. Some of the slides have value errors. Explanations for the programming assignments could be better.

교육 기관: Anubhav B

2016년 11월 7일

The course is very insightful and very helpful for the data mining studies at university courses.

교육 기관: Ridowati G

2021년 1월 24일

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

교육 기관: PREETAM R

2020년 7월 28일

Covers great deal of topics and various aspects of clustering

교육 기관: shane

2017년 9월 7일

Very detailed introduction of Clustering techniques.