Clustering Algorithms Resources

Papers

Stream Clustering

• slides: www.cse.msu.edu/~cse902/S14/ppt/Stream%20Clustering.pptx

PAC-Bayesian Online Clustering

• arxiv: http://arxiv.org/abs/1602.00522

Semi-supervised K-means++

• arxiv: http://arxiv.org/abs/1602.00360

Compressive Spectral Clustering

• arxiv: http://arxiv.org/abs/1602.02018

Interactive Bayesian Hierarchical Clustering

• arxiv: http://arxiv.org/abs/1602.03258

k-Means Clustering Is Matrix Factorization

• arxiv: http://arxiv.org/abs/1512.07548
• note: http://blog.csdn.net/cyh_24/article/details/50408884

Practical Introduction to Clustering Data

• arxiv: http://arxiv.org/abs/1602.05124

Rényi divergence minimization based co-regularized multiview clustering

• paper: http://rd.springer.com.sci-hub.io/article/10.1007/s10994-016-5543-2?wt_mc=internal.event.1.SEM.ArticleAuthorOnlineFirst

Consistent Algorithms for Clustering Time Series

• paper: http://jmlr.org/papers/v17/khaleghi16a.html

Hybridization of Expectation-Maximization and K-Means Algorithms for Better Clustering Performance

• arxiv: http://arxiv.org/abs/1603.07879

Books

• intro: 《Machine Learning with R - Second Edition》by Brett Lantz
• book: https://www.packtpub.com/books/content/introduction-clustering-and-unsupervised-learning

Blogs

Finding the K in K-means by Parametric Bootstrap

• blog: http://www.win-vector.com/blog/2016/02/finding-the-k-in-k-means-by-parametric-bootstrap/

Random walk vectors for clustering

• part I – similarity between objects: http://int8.io/random-walk-vectors-for-clustering-part-i-similarity-between-objects/
• part II – perspective switch: http://int8.io/random-walk-vectors-for-clustering-part-ii-perspective-switch/
• part III: http://int8.io/random-walk-vectors-for-clustering-iii/
• final: http://int8.io/random-walk-vectors-for-clustering-final/

A comparison between PCA and hierarchical clustering

http://www.kdnuggets.com/2016/02/qlucore-comparison-pca-hierarchical-clustering.html

Visualization of Centroid Movements for K-Means Clustering

http://web.cecs.pdx.edu/~lane7/

K-Means Clustering on Handwritten Digits

http://johnloeber.com/docs/kmeans.html

Improved Seeding For Clustering With K-Means++ (★★★★★)

https://datasciencelab.wordpress.com/2014/01/15/improved-seeding-for-clustering-with-k-means/

Spectral Clustering – How Math is Redefining Decision Making

http://www.datasciencecentral.com/profiles/blogs/spectral-clustering-how-math-is-redefining-decision-making?overrideMobileRedirect=1

Codes

MusicMappr: Find patterns in your favorite songs and remix them on the fly!

• intro: MusicMappr finds chunks of songs that are similar, and clusters them accordingly. You can visualize these clusters and play them back at will. This is for music lovers who are curious about the structures inherent to their favorite songs.
• github: https://github.com/fatsmcgee/MusicMappr