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Anomaly detection on high dimensional Data using k means/SVM/LOF? [closed]
I am working on one Anomaly detection problem (unsupervise problem)
Data set have
1) 15 columns and around 8k rows , including normal and abnormal(outlier ) rows, without label , all are numeric
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R - high dimension data using k means clustering [closed]
The dataset is 1000(observations) x 700(variables), After using pca to do dimension reduction, PC150 explained 85% Variance, so I use this (1000 x 150) data to do k means clustering.
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