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https://issues.apache.org/jira/browse/IGNITE-9283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aleksey Zinoviev updated IGNITE-9283:
-------------------------------------
Description:
Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform]
Please look at the MinMaxScaler or Normalization packages in preprocessing
package.
Add classes if required
1) Preprocessor
2) Trainer
3) custom PartitionData if shuffling is a step of algorithm
Requirements for successful PR:
# PartitionedDataset usage
# Trainer-Model paradigm support
# Tests for Model and for Trainer (and other stuff)
# Example of usage with small, but famous dataset like IRIS, Titanic or House
Prices
# Javadocs/codestyle according guidelines
was:
Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform]
Please look at the MinMaxScaler or Normalization packages in preprocessing
package.
Add classes if required
1) Preprocessor
2) Trainer
3) custom PartitionData if shuffling is a step of algorithm
> [ML] Add Discrete Cosine preprocessor
> -------------------------------------
>
> Key: IGNITE-9283
> URL: https://issues.apache.org/jira/browse/IGNITE-9283
> Project: Ignite
> Issue Type: Sub-task
> Components: ml
> Reporter: Aleksey Zinoviev
> Priority: Major
>
> Add [https://en.wikipedia.org/wiki/Discrete_cosine_transform]
> Please look at the MinMaxScaler or Normalization packages in preprocessing
> package.
> Add classes if required
> 1) Preprocessor
> 2) Trainer
> 3) custom PartitionData if shuffling is a step of algorithm
>
> Requirements for successful PR:
> # PartitionedDataset usage
> # Trainer-Model paradigm support
> # Tests for Model and for Trainer (and other stuff)
> # Example of usage with small, but famous dataset like IRIS, Titanic or
> House Prices
> # Javadocs/codestyle according guidelines
>
>
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