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Overview of CatBoost

CatBoost is a machine learning algorithm that uses gradient boosting on decision trees. It is available as an open source library.

Main advantages of CatBoost:
  • Superior quality when compared with other libraries.
  • Support for both numerical
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    Numeric. Examples are the height (“182”, “173”), or any binary feature (“0”, “1”).

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    and categorical
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    Categorical (cat). Such features can take one of a limited number of possible values. These values are usually fixed. Examples are the musical genre (“rock”, “indie”, “pop”) and the musical style (“dance”, “classical”).

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    features.
  • Data visualization tools included.

The following implementations are available: