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返回到 数据挖掘中的聚类分析

學生對 伊利诺伊大学香槟分校 提供的 数据挖掘中的聚类分析 的評價和反饋

4.5
373 個評分
58 條評論

課程概述

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
2018年12月17日

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
2019年11月6日

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

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26 - 数据挖掘中的聚类分析 的 50 個評論(共 58 個)

創建者 Dr. P N

2020年10月14日

A wonderful learning experience !

創建者 Pavan G

2017年10月2日

Explained with nice examples

創建者 Leela P

2017年1月16日

Very useful and well taught

創建者 AJETUNMOBI O

2017年5月1日

Clustering demytified

創建者 Ankit

2020年2月12日

Fantastic course

創建者 Christopher D

2016年11月8日

Great course!

創建者 VIDUSHI M

2019年3月17日

Excellent!

創建者 KRUPAL J K

2019年4月9日

VERY GOOD

創建者 Oren

2017年6月7日

Very good

創建者 Hernan C V

2017年7月1日

Awesome!

創建者 vaseem a

2019年4月8日

awesome

創建者 Alan J R

2020年2月20日

great!

創建者 Valerie P

2017年7月11日

E

創建者 geoffrey a

2017年9月2日

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.

創建者 David M L H

2020年6月12日

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.

創建者 Cassius d O P

2021年4月17日

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.

創建者 GANG L

2018年1月26日

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.

創建者 Devender B

2019年3月10日

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.

創建者 Umesh G

2019年4月28日

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

創建者 Alexander S

2019年12月16日

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

創建者 Anubhav B

2016年11月7日

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

創建者 Ridowati G

2021年1月24日

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

創建者 PREETAM R

2020年7月28日

Covers great deal of topics and various aspects of clustering

創建者 shane

2017年9月7日

Very detailed introduction of Clustering techniques.

創建者 Venuu M

2019年4月11日

The course helped me a lot. I loved this course