ensemble

probly.method.ensemble(base: Predictor[In, Out], num_members: int, reset_params: bool = True) → EnsemblePredictor[In, Out]

Create an ensemble predictor from a base predictor based on [LPB17].

Parameters:

• base – The base model to be used for the ensemble.

• num_members – The number of members in the ensemble.

• reset_params – Whether to reset the parameters of each member.

Returns:

The ensemble predictor.

Examples using probly.method.ensemble

Quantile Regression Conformal Prediction — PyTorch

Quantile Regression Conformal Prediction — PyTorch

Depth estimation uncertainty with transformers

Depth estimation uncertainty with transformers

Forecast uncertainty with transformers

Forecast uncertainty with transformers

LoRA adapter ensembles with peft

LoRA adapter ensembles with peft

Uncertainty for Hugging Face transformers

Uncertainty for Hugging Face transformers

Ensemble Ordinal Classification Uncertainty

Ensemble Ordinal Classification Uncertainty

Ensemble Regression Uncertainty

Ensemble Regression Uncertainty