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https://issues.apache.org/jira/browse/SPARK-11302?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-11302:
----------------------------------
Assignee: Sean Owen
Affects Version/s: 1.6.0
1.3.1
1.4.1
1.5.1
Target Version/s: 1.4.1, 1.3.2, 1.5.2, 1.6.0
Description:
I have been trying to apply an Anomaly Detection model using Spark MLib.
As an input, I feed the model with a mean vector and a Covariance matrix.
,assuming my features contain Co-variance.
Here are my input for the model ,and the model returns zero for each data
point for this 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
Conversely, for the non covariance case, represented by this matrix ,the
model is working and returns results as expected
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
was:
I have been trying to apply an Anomaly Detection model using Spark MLib.
As an input, I feed the model with a mean vector and a Covariance matrix.
,assuming my features contain Co-variance.
Here are my input for the model ,and the model returns zero for each data
point for this 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
Conversely, for the non covariance case, represented by this matrix ,the
model is working and returns results as expected
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
> Multivariate Gaussian Model with Covariance matrix returns incorrect answer
> in some cases
> --------------------------------------------------------------------------------------------
>
> Key: SPARK-11302
> URL: https://issues.apache.org/jira/browse/SPARK-11302
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.3.1, 1.4.1, 1.5.1, 1.6.0
> Reporter: eyal sharon
> Assignee: Sean Owen
> Priority: Minor
>
> I have been trying to apply an Anomaly Detection model using Spark MLib.
> As an input, I feed the model with a mean vector and a Covariance matrix.
> ,assuming my features contain Co-variance.
> Here are my input for the model ,and the model returns zero for each data
> point for this 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
> Conversely, for the non covariance case, represented by this matrix ,the
> model is working and returns results as expected
> 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
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