PGBM
latest

Contents:

  • Installation
  • Quick Start
  • Features
  • Parameters (Torch backend)
  • Parameters (Scikit-learn backend)
  • Examples
  • Distributed Learning
  • Function reference
  • Support
PGBM
  • Index
  • Edit on GitHub

Index

C | D | F | L | M | O | P | R | S | T

C

  • crps_ensemble() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)
    • (pgbm.torch.PGBMRegressor method)

D

  • DistPGBM (class in pgbm.torch)

F

  • fit() (pgbm.torch.PGBMRegressor method)

L

  • load() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)

M

  • module
    • pgbm.torch

O

  • optimize_distribution() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)

P

  • permutation_importance() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)
  • PGBM (class in pgbm.torch)
  • pgbm.torch
    • module
  • PGBMRegressor (class in pgbm.torch)
  • predict() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)
    • (pgbm.torch.PGBMRegressor method)
  • predict_dist() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)
    • (pgbm.torch.PGBMRegressor method)

R

  • rmseloss_metric() (pgbm.torch.PGBMRegressor method)

S

  • save() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)
    • (pgbm.torch.PGBMRegressor method)
  • score() (pgbm.torch.PGBMRegressor method)

T

  • train() (pgbm.torch.DistPGBM method)
    • (pgbm.torch.PGBM method)

© Copyright 2021-2023, Olivier Sprangers, AirLab. Revision 58dc354c.

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