Difference between revisions of "Principal Component Analysis (PCA)"
m (BPeat moved page Principal Components Analysis (PCA)-based Anomaly Detection to Principle Component Analysis (PCA) without leaving a redirect) |
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* [[AI Solver]] | * [[AI Solver]] | ||
* [[...find outliers]] | * [[...find outliers]] | ||
| + | * [[Dimensional Reduction Algorithms]] | ||
* [http://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/pca-based-anomaly-detection PCA-Based Anomaly Detection | Microsoft] | * [http://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/pca-based-anomaly-detection PCA-Based Anomaly Detection | Microsoft] | ||
Revision as of 07:07, 29 July 2018
PCA-based anomaly detection - the vast majority of the data falls into a stereotypical distribution; points deviating dramatically from that distribution are suspect Keep it Simple : Machine Learning & Algorithms for Big Boys | Dinesh Chandrasekar
PCA
