README.md 1 KB
Newer Older
Saman Nia's avatar
Final  
Saman Nia committed
1
# Deep Learning Clustering;
Martin Perdacher's avatar
Martin Perdacher committed
2

Saman Nia's avatar
Final  
Saman Nia committed
3
In this report, we try to optimize an idea which already has been presented under title " Learning Deep Representations for Graph clustering" by F. Tian, B. Gao, Q. Cui, E. Chen, T. Liu. The idea is described as follows: “modeling a simple method which embedding the similarity graph by deep autoencoder with sparsity penalty, then runs the K-Means algorithm on the embedding graph to obtain the clustering result”. However, although our model is based on the original idea, but the graph similarity and the loss function and the model training methods are different. We also compare our results with the two previous results based on the recent papers ( F. Tian, B. Gao, Q. Cui, E. Chen, T. Liu, 2014), (S. Cao, W. Lu, Q, Xu, 2016) on the same datasets. 
Saman Nia's avatar
Final  
Saman Nia committed
4
Below you will see a autoencoder embedded 3NG(3 groups of the 20-newsgroups dataset)data into two dimensions:
Saman Nia's avatar
Saman Nia committed
5

Saman Nia's avatar
Final  
Saman Nia committed
6
![Alt text](https://github.com/saman-nia/Autoencoder_Clustering/blob/master/Visualizations/2D_Embedded.png?raw=true "Title")