public abstract static class SupervisedModel.SupervisedParameters extends Model.Parameters
| Modifier and Type | Field and Description |
|---|---|
boolean |
_balance_classes
Should the minority classes be upsampled to balance the class
distribution?
|
float |
_max_after_balance_size
When classes are being balanced, limit the resulting dataset size to
the specified multiple of the original dataset size.
|
java.lang.String |
_response_column
Supervised models have an expected response they get to train with!
|
boolean |
_toEnum
Convert the response column to an enum (forcing a classification
instead of a regression) as needed.
|
_destination_key, _dropNA20Cols, _ignored_columns, _score_each_iteration, _train, _valid| Constructor and Description |
|---|
SupervisedModel.SupervisedParameters() |
| Modifier and Type | Method and Description |
|---|---|
long |
checksum() |
defaultDropNA20Cols, lock_frames, train, unlock_frames, validclone, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, write_impl, write, writeExternal, writeHTML_impl, writeHTML, writeJSON_impl, writeJSONpublic java.lang.String _response_column
public boolean _toEnum
public boolean _balance_classes
public float _max_after_balance_size
public SupervisedModel.SupervisedParameters()
public long checksum()
checksum in class Model.Parameters