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Spectral clustering - Houston ML Meetup

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Yan Xu
Yan Xu

Introduction to spectral clustering at Houston Machine Learning meetup

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Clustering for New Discovery in Data Part 2 Houston Machine Learning Meetup
2 SCR© https://energyconferencenetwork.com/machine-learning-oil-gas-2017/ 20% off, PROMO code: HML
3 SCR© Roadmap: Method • Tour of machine learning algorithms (1 session) • Feature engineering (1 session) – Feature selection - Yan • Supervised learning (4 sessions) – Regression models -Yan – SVM and kernel SVM - Yan – Tree-based models - Dario – Bayesian method - Xiaoyang – Ensemble models - Yan • Unsupervised learning (3 sessions) – K-means clustering – DBSCAN - Cheng – Mean shift – Agglomerative clustering – Kunal – Spectral clustering – Yan – Dimension reduction for data visualization - Yan • Deep learning (4 sessions) _ Neural network – From neural network to deep learning – Convolutional neural network – Train deep nets with open-source tools
4 SCR© Roadmap: Application • Business analytics • Recommendation system • Natural language processing • Computer vision • Energy industry
5 SCR© Clustering Algorithm • K-Means (King of clustering, many variants) • DBSCAN (group neighboring points) • Hierarchical clustering (a hierarchical structure, multiple levels) • Mean shift (locating the maxima of density) • Spectral clustering (cares about connectivity instead of proximity) • Expectation Maximization (k-means is a variant of EM) • Latent Dirichlet Allocation (natural language processing) ……
6 SCR© Agenda • Hierarchical clustering • Mean shift • Spectral clustering
7 SCR© Referenece: http://www.cvl.isy.liu.se:82/education/graduate/spectral-clustering.html Spectral Clustering
8 SCR©
9 SCR©
10 SCR©
11 SCR© Add noise to A
12 SCR©
13 SCR© Modification I
14 SCR© Min-cut problem
15 SCR© Modification II
16 SCR©
17 SCR© Ratio-cut problem
18 SCR©
19 SCR©
20 SCR©
21 SCR© Normalized spectral clustering Make the clustering less sensitive to the cluster sizes
22 SCR© Normalized symmetric spectral clustering Less sensitive to the cluster sizes and better separation of clusters
23 SCR©
24 SCR©
25 SCR©
26 SCR© Summary • Application of spectral clustering in computer vision
27 SCR© Roadmap: Method • Tour of machine learning algorithms (1 session) • Feature engineering (1 session) – Feature selection - Yan • Supervised learning (4 sessions) – Regression models -Yan – SVM and kernel SVM - Yan – Tree-based models - Dario – Bayesian method - Xiaoyang – Ensemble models - Yan • Unsupervised learning (3 sessions) – K-means clustering – DBSCAN - Cheng – Mean shift – Agglomerative clustering – Spectral clustering – Kunal, Yan – Dimension reduction for data visualization - Yan • Deep learning (4 sessions) _ Neural network – From neural network to deep learning – Convolutional neural network – Train deep nets with open-source tools
28 SCR© https://energyconferencenetwork.com/machine-learning-oil-gas-2017/ 20% off, PROMO code: HML
29 SCR© Thank you Slides will be posted on slide share: http://www.slideshare.net/xuyangela
30 SCR© ParkingWe are here @ W205 Enter

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