library(tfdatasets)
data(hearts)
$thal <- as.integer(as.factor(hearts$thal)) - 1L
hearts
<- tensor_slices_dataset(hearts) %>% dataset_batch(32)
hearts
# use the formula interface
<- feature_spec(hearts, target ~ thal) %>%
spec step_categorical_column_with_identity(thal, num_buckets = 5)
<- fit(spec)
spec_fit <- hearts %>% dataset_use_spec(spec_fit) final_dataset
step_categorical_column_with_identity
Create a categorical column with identity
Description
Use this when your inputs are integers in the range [0-num_buckets)
.
Usage
step_categorical_column_with_identity(
spec,
...,
num_buckets, default_value = NULL
)
Arguments
Arguments | Description |
---|---|
spec | A feature specification created with feature_spec() . |
… | Comma separated list of variable names to apply the step. selectors can also be used. |
num_buckets | Range of inputs and outputs is [0, num_buckets) . |
default_value | If NULL , this column’s graph operations will fail for out-of-range inputs. Otherwise, this value must be in the range [0, num_buckets) , and will replace inputs in that range. |
Value
a FeatureSpec
object.
Examples
See Also
steps for a complete list of allowed steps. Other Feature Spec Functions: dataset_use_spec()
, feature_spec()
, fit.FeatureSpec()
, step_bucketized_column()
, step_categorical_column_with_hash_bucket()
, step_categorical_column_with_vocabulary_file()
, step_categorical_column_with_vocabulary_list()
, step_crossed_column()
, step_embedding_column()
, step_indicator_column()
, step_numeric_column()
, step_remove_column()
, step_shared_embeddings_column()
, steps