ai.catboost.spark.package.scala Maven / Gradle / Ivy
package ai.catboost
import ru.yandex.catboost.spark.catboost4j_spark.core.src.native_impl
/** CatBoost is a machine learning algorithm that uses gradient boosting on decision trees.
*
* ==Overview==
* This package provides classes that implement interfaces from
* [[https://spark.apache.org/mllib/ Apache Spark Machine Learning Library (MLLib)]].
*
* For binary and multi- classification problems use [[CatBoostClassifier]],
* for regression use [[CatBoostRegressor]].
*
* These classes implement usual `fit` method of [[org.apache.spark.ml.Predictor]] that accept a single
* [[org.apache.spark.sql.DataFrame]] for training, but you can also use other `fit` method that accepts
* additional datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's
* other APIs.
*
* This package also contains [[Pool]] class that is CatBoost's abstraction of a dataset.
* It contains additional information compared to simple [[org.apache.spark.sql.DataFrame]].
*
* It is also possible to create [[Pool]] with quantized features before training by calling `quantize` method.
* This is useful if this dataset is used for training multiple times and quantization parameters do not
* change. Pre-quantized [[Pool]] allows to cache quantized features data and so do not re-run
* feature quantization step at the start of an each training.
*
* Detailed documentation is available on [[https://catboost.ai/docs/]]
*/
package object spark {
type EModelType = native_impl.EModelType
type ECtrTableMergePolicy = native_impl.ECtrTableMergePolicy
}