"Here's a preliminary data mining analysis of musical social networking service Last.fm. An automated classification into clusters or sub populations with related musical genres reveals the structure of musical preferences among the users in a relatively large sample population. Musical tag clouds are adopted to characterise users and populations, which adds a highly descriptive value and aids with the interpretation of the results."
We observed that generally the embedding representation is very rich and information dense. For example, reducing the dimensionality of the inputs using SVD or PCA, even by 10%, generally results in worse downstream performance on specific tasks.
Die Grundannahme für die Verwendung der PCA zur Clusteranalyse und Dimensionsreduktion lautet: Die Richtungen mit der größten Streuung (Varianz) beinhalten die meiste Information.
The Matlab Toolbox for Dimensionality Reduction contains Matlab implementations of a large number of techniques for dimensionality reduction. A large number of implementations was developed from scratch, whereas other implementations are improved versions
Modular toolkit for Data Processing (MDP) is a Python data processing framework. Implemented algorithms include: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Slow Feature Analysis (SFA), Growing Neural Gas (GNG), Factor Analys
C. Lu, T. Zhang, X. Du, и C. Li. Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on, 5, стр. 3084-3087 vol.5. (2004)