N2D: (Not Too) Deep Clustering

前陣子再找sensor data的機器學習分類方式, 看到這個N2D

之後來研究看看(!?)

Not too deep clustering is a state of the art "deep" clustering technique, in which first, the data is embedded using an autoencoder. Then, instead of clustering that using some deep clustering network, we use a manifold learner to find the underlying (local) manifold in the embedding. Then, we cluster that manifold. In the paper, this was shown to produce high quality clusters without the standard extreme feature engineering required for clustering.

Project description
https://pypi.org/project/n2d/

Welcome to n2d’s documentation!
https://n2d.readthedocs.io/en/latest/


https://github.com/rymc/n2d


Paper
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding
https://arxiv.org/abs/1908.05968