Features
- Add support for distributed training and distributed hyper-parameter tuning
in the OSS build. See
https://www.tensorflow.org/decision_forests/distributed_training
- Setting "subsample" is enough enable random subsampling (to need to also set
"sampling_method=RANDOM").
- Add "min_vocab_frequency" argument in "FeatureUsage" to control the minimum
frequency of categorical items.
- Add "override_global_imputation_value" argument in "FeatureUsage" to
override the value used for global imputation of missing value by the
global-imputation algorithm.
- The Tuner argument "use_predefined_hps" automatically configures the set of
hyper-parameters to explore during automatic hyper-parameter tuning.
- Replaces the MEAN_MIN_DEPTH variable importance with INV_MEAN_MIN_DEPTH.
- Add option to forbid model inference with the slow inference engine.
Fix
- Automatic documentation generation for RandomForestModel and other classes.