• Installation
    • Overview
    • Python package installation
    • CatBoost for Apache Spark installation
    • R package installation
    • Command-line version binary
    • Build from source
  • Key Features
  • Training parameters
  • Python package
  • CatBoost for Apache Spark
  • R package
  • Command-line version
  • Applying models
  • Objectives and metrics
  • Model analysis
  • Data format description
  • Parameter tuning
  • Speeding up the training
  • Data visualization
  • Algorithm details
  • FAQ
  • Educational materials
  • Development and contributions
  • Contacts

Supported metrics for output during the training

  • RMSE

  • Logloss

  • MAE

  • CrossEntropy

  • Quantile

  • LogLinQuantile

  • Lq

  • MultiRMSE

  • MultiClass

  • MultiClassOneVsAll

  • MultiLogloss

  • MultiCrossEntropy

  • MAPE

  • Poisson

  • PairLogit

  • PairLogitPairwise

  • QueryRMSE

  • QuerySoftMax

  • Tweedie

  • SMAPE

  • Recall

  • Precision

  • F

  • F1

  • TotalF1

  • Accuracy

  • BalancedAccuracy

  • BalancedErrorRate

  • Kappa

  • WKappa

  • LogLikelihoodOfPrediction

  • AUC

  • QueryAUC

  • R2

  • FairLoss

  • NumErrors

  • MCC

  • BrierScore

  • HingeLoss

  • HammingLoss

  • ZeroOneLoss

  • MSLE

  • MedianAbsoluteError

  • Huber

  • Expectile

  • MultiRMSE

  • PairAccuracy

  • AverageGain

  • PFound

  • NDCG

  • DCG

  • FilteredDCG

  • NormalizedGini

  • PrecisionAt

  • RecallAt

  • MAP

  • CtrFactor