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https://issues.apache.org/jira/browse/IGNITE-9282?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aleksey Zinoviev updated IGNITE-9282:
-------------------------------------
Description:
Naive Bayes classifiers are a family of simple probabilistic classifiers based
on applying Bayes' theorem with strong (naive) independence assumptions between
the features.
So we want to add this algorithm to Apache Ignite ML module.
Ideally, implementation should support both multinomial naive Bayes and
Bernoulli naive Bayes.
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:
Naive Bayes classifiers are a family of simple probabilistic classifiers based
on applying Bayes' theorem with strong (naive) independence assumptions between
the features.
So we want to add this algorithm to Apache Ignite ML module.
Ideally, implementation should support both multinomial naive Bayes and
Bernoulli naive Bayes.
> [ML] Add Naive Bayes classifier
> -------------------------------
>
> Key: IGNITE-9282
> URL: https://issues.apache.org/jira/browse/IGNITE-9282
> Project: Ignite
> Issue Type: Sub-task
> Components: ml
> Reporter: Aleksey Zinoviev
> Priority: Major
>
> Naive Bayes classifiers are a family of simple probabilistic classifiers
> based on applying Bayes' theorem with strong (naive) independence assumptions
> between the features.
> So we want to add this algorithm to Apache Ignite ML module.
> Ideally, implementation should support both multinomial naive Bayes and
> Bernoulli naive Bayes.
> 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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