Tabular Regressor (Experimental)¶
Skorch Table Regressor https://skorch.readthedocs.io/en/stable/regressor.html
Documentation¶
Attributes¶
- history_
Model training history
Definition¶
Output ports¶
- model model
Model
Configuration¶
- Number of categories for each categorical column (cat_dims)
Number of categories for each categorical column
- Embedding dimension for each categorical column (cat_emb_dim)
Embedding dimension for each categorical column
- Ids of categorical columns (cat_idxs)
Ids of categorical columns
- Cross validation (cross_validation)
Cross validation
- Early stopping (early_stopping)
Early stopping
- Learning rate (lr)
Learning rate
- Maximum number of epochs (max_epochs)
The number of epochs to train for each fit.
- Optimizer (optimizer)
The optimizer (update rule) used to optimize the module
Implementation¶
- class node_neuralnetwork.TabularRegressor[source]