tabular_learner: Tabular learner
In EagerAI/fastai: Interface to 'fastai'

tabular_learner

R Documentation

Tabular learner

Description

Get a 'Learner' using 'dls', with 'metrics', including a 'TabularModel' created using the remaining params.

Usage

tabular_learner(
  dls,
  layers = NULL,
  emb_szs = NULL,
  config = NULL,
  n_out = NULL,
  y_range = NULL,
  loss_func = NULL,
  opt_func = Adam(),
  lr = 0.001,
  splitter = trainable_params(),
  cbs = NULL,
  metrics = NULL,
  path = NULL,
  model_dir = "models",
  wd = NULL,
  wd_bn_bias = FALSE,
  train_bn = TRUE,
  moms = list(0.95, 0.85, 0.95)
)

Arguments

`dls`	It is a DataLoaders object.
`layers`	layers
`emb_szs`	emb_szs
`config`	config
`n_out`	n_out
`y_range`	y_range
`loss_func`	It can be any loss function you like.
`opt_func`	It will be used to create an optimizer when Learner.fit is called.
`lr`	It is learning rate.
`splitter`	It is a function that takes self.model and returns a list of parameter groups (or just one parameter group if there are no different parameter groups)
`cbs`	It is one or a list of Callbacks to pass to the Learner.
`metrics`	It is an optional list of metrics, that can be either functions or Metrics.
`path`	İt is used to save and/or load models.Often path will be inferred from dls, but you can override it or pass a Path object to model_dir. Make sure you can write in path/model_dir!
`model_dir`	İt is used to save and/or load models.Often path will be inferred from dls, but you can override it or pass a Path object to model_dir. Make sure you can write in path/model_dir!
`wd`	It is the default weight decay used when training the model.
`wd_bn_bias`	It controls if weight decay is applied to BatchNorm layers and bias.
`train_bn`	It controls if BatchNorm layers are trained even when they are supposed to be frozen according to the splitter.
`moms`	The default momentums used in Learner.fit_one_cycle.