package booster
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Type Members
- trait Booster[D] extends Model
- case class BoosterDataset(original: Dataset, data: Array[Double], labels: Array[Double], groups: Array[Int], rows: Int, cols: Int, featureNames: Array[String]) extends Product with Serializable
- case class CatboostBooster(booster: CatBoostModel, bytes: Array[Byte]) extends Booster[String] with Product with Serializable
- case class CatboostOptions(trees: Int = 100, learningRate: Double = 0.1, ndcgCutoff: Int = 10, maxDepth: Int = 8, randomSeed: Int = math.abs(Random.nextInt()), objective: String = "QueryRMSE", loggingLevel: String = "Verbose", earlyStopping: Option[Int] = None, boostingType: String = "Plain") extends BoosterOptions with Product with Serializable
- case class LightGBMBooster(model: LGBMBooster) extends Booster[LGBMDataset] with Logging with Product with Serializable
- case class LightGBMOptions(trees: Int = 100, learningRate: Double = 0.1, ndcgCutoff: Int = 10, maxDepth: Int = 8, randomSeed: Int = math.abs(Random.nextInt()), numLeaves: Int = 16, featureFraction: Double = 1.0, earlyStopping: Option[Int] = None) extends BoosterOptions with Product with Serializable
- case class XGBoostBooster(model: ml.dmlc.xgboost4j.java.Booster, featureTypes: Array[String]) extends Booster[DMatrix] with Logging with Product with Serializable
- case class XGBoostOptions(trees: Int = 100, learningRate: Double = 0.1, ndcgCutoff: Int = 10, maxDepth: Int = 8, randomSeed: Int = math.abs(Random.nextInt()), subsample: Double = 1.0, earlyStopping: Option[Int] = None, treeMethod: String = "exact") extends BoosterOptions with Product with Serializable
Value Members
- object Booster
- object CatboostBooster extends BoosterFactory[String, CatboostBooster, CatboostOptions] with Serializable
- object LightGBMBooster extends BoosterFactory[LGBMDataset, LightGBMBooster, LightGBMOptions] with Logging with Serializable
- object XGBoostBooster extends BoosterFactory[DMatrix, XGBoostBooster, XGBoostOptions] with Logging with Serializable