Creates an empty Gradient Tree Boost classifier.

ee.Classifier.smileGradientTreeBoost(numberOfTrees, shrinkage, samplingRate, maxNodes, loss, seed)Classifier

The number of decision trees to create.

shrinkageFloat, default: 0.005

The shrinkage parameter in (0, 1] controls the learning rate of procedure.

samplingRateFloat, default: 0.7

The sampling rate for stochastic tree boosting.

maxNodesInteger, default: null

The maximum number of leaf nodes in each tree. If unspecified, defaults to no limit.

lossString, default: "LeastAbsoluteDeviation"

Loss function for regression. One of: LeastSquares, LeastAbsoluteDeviation, Huber.

seedInteger, default: 0

The randomization seed.