Choosing Statistical Model


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Machine Learning Algorithm timeline

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I came across this interesting plot showing different algorithms, their inventors and their usage trend. Clearly, Neural Networks and Deep Belief Networks have revived and have a way to go. There is an interesting discussion on Quora, which users of these algorithms may be interested in: http://www.quora.com/Will-deep-learning-make-other-Machine-Learning-algorithms-obsolete
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Anomaly Detection

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In this post i'd like to share references and articles which I came across while learning Anomaly Detection Techniques like blogs/ papers / patents/ Wikipedia information etc. Popular Anomaly Detection Techniques: Density-based techniques (k-nearest neighbor, local outlier factor, and many more variations of this concept).  Knorr, E. M.; Ng, R. T.; Tucakov, V. (2000). "Distance-based outliers: Algorithms and applications". The VLDB Journal the International Journal on Very Large Data Bases 8 (3–4): 237. doi:10.1007/s007780050006.  Ramaswamy, S.; Rastogi, R.; Shim, K. (2000). Efficient algorithms for mining outliers from large data sets. Proceedings of the 2000 ACM SIGMOD international conference on Management of data - SIGMOD '00. p. 427. doi:10.1145/342009.335437. ISBN 1581132174. Angiulli, F.; Pizzuti, C. (2002). Fast Outlier Detection in High Dimensional Spaces. Principles of Data Mining and Knowledge Discovery. Lecture Notes in Computer Sci
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