library(tfdatasets)
data(hearts)
hearts <- tensor_slices_dataset(hearts) %>% dataset_batch(32)
# use the formula interface
spec <- feature_spec(hearts, target ~ age) %>%
step_numeric_column(age)
spec_fit <- fit(spec)
spec_fit fit.FeatureSpec
Fits a feature specification.
Description
This function will fit the specification. Depending on the steps added to the specification it will compute for example, the levels of categorical features, normalization constants, etc.
Usage
## S3 method for class 'FeatureSpec'
fit(object, dataset = NULL, ...) Arguments
| Arguments | Description |
|---|---|
| object | A feature specification created with feature_spec(). |
| dataset | (Optional) A TensorFlow dataset. If NULL it will use the dataset provided when initilializing the feature_spec. |
| … | (unused) |
Value
a fitted FeatureSpec object.
Examples
See Also
feature_spec()to initialize the feature specification.dataset_use_spec()to create a tensorflow dataset prepared to modeling.steps to a list of all implemented steps.
Other Feature Spec Functions:
dataset_use_spec(),feature_spec(),step_bucketized_column(),step_categorical_column_with_hash_bucket(),step_categorical_column_with_identity(),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