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https://issues.apache.org/jira/browse/FLINK-2379?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15045057#comment-15045057
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ASF GitHub Bot commented on FLINK-2379:
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Github user sachingoel0101 commented on the pull request:
https://github.com/apache/flink/pull/1032#issuecomment-162550968
Hi @chiwanpark, thanks for picking this up. :)
Since a `Vector` might contain discrete fields as well as continuous
fields, we need to have a `FieldStats` object which can cover both types. To
prevent the need of casting from `FieldStats` to `ContinuousFieldStats` and
`DiscreteFieldStats` in case there is an abstract class `FieldStats`, I
supported them both in a single class.
What do you think would be the best solution here?
As for your second point regarding `T <: Vector`, will fix it.
> Add methods to evaluate field wise statistics over DataSet of vectors.
> ----------------------------------------------------------------------
>
> Key: FLINK-2379
> URL: https://issues.apache.org/jira/browse/FLINK-2379
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Sachin Goel
> Assignee: Sachin Goel
>
> Design methods to evaluate statistics over dataset of vectors.
> For continuous fields, Minimum, maximum, mean, variance.
> For discrete fields, Class counts, Entropy, Gini Impurity.
> Further statistical measures can also be supported. For example, correlation
> between two series, computing the covariance matrix, etc.
> [These are currently the things Spark supports.]
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