Problem with applying Multivariate Gaussian Model

[Eyal Sharon <ey...@scene53.com>]

  Hi ,

I have been trying to apply an Anomaly Detection model  using Spark MLib.
I am using this library

org.apache.spark.mllib.stat.distribution.MultivariateGaussian


As an input, I give the model a mean vector and a Covariance matrix,
assuming my features have Covariance , hence the covariane matrix has
all non zero elements.

The model returns zero for each data point.

While using a model with out covariance, meaning the matrix has zero
in all element except the diagonal. The model is working.

Now, there is a little documentation for this model.

Does anyone have experience applying this model ?

any reference will be welcome too

These are the model input


*mu vector - *

1054.8, 1069.8, 1.3 ,1040.1

*cov matrix - *

165496.0 , 167996.0,  11.0 , 163037.0
167996.0,  170631.0,  19.0,  165405.0
11.0,           19.0 ,         0.0,   2.0
163037.0,   165405.0     2.0 ,  160707.0

*and for non covariance case *

165496.0,  0.0 ,           0.0,   0.0
0.0,           170631.0,   0.0,   0.0
0.0 ,           0.0 ,           0.8,   0.0
0.0 ,           0.0,            0.0,  160594.2


Thanks !


Eyal

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