public interface ConnectorConstants
Modifier and Type | Field and Description |
---|---|
static String |
PARAM_APPLY_WEIGHTING
Whether to turn on instance weighting.
|
static String |
PARAM_BIPARTITION_THRESHOLD
In case of multi-labeling, the threshold used to create bipartitions from rankings
|
static String |
PARAM_DATA_WRITER_CLASS
The data writer class to be used for writing features
|
static String |
PARAM_ENFORCE_MATCHING_FEATURES
If the matching of features in training and testing phase shall be enforced - this will slow
down experiment execution considerably if activated
|
static String |
PARAM_FEATURE_EXTRACTORS
Array of feature extractors to be used
|
static String |
PARAM_FEATURE_FILTERS
Array of feature filters to be used
|
static String |
PARAM_FEATURE_MODE
The feature mode, e.g. document, pair, unit, or sequence
|
static String |
PARAM_IS_TESTING
Whether we are extracting for training or testing.
|
static String |
PARAM_LEARNING_MODE
The learning mode, e.g. single-label, multi-label or regression
|
static String |
PARAM_OUTCOMES
Array of outcomes
|
static String |
PARAM_REQUIRED_TYPES
If a sparse feature representation shall be used
|
static String |
PARAM_USE_SPARSE_FEATURES
If a sparse feature representation shall be used
|
static final String PARAM_FEATURE_EXTRACTORS
static final String PARAM_OUTCOMES
static final String PARAM_FEATURE_FILTERS
static final String PARAM_DATA_WRITER_CLASS
static final String PARAM_LEARNING_MODE
static final String PARAM_FEATURE_MODE
static final String PARAM_BIPARTITION_THRESHOLD
static final String PARAM_IS_TESTING
static final String PARAM_APPLY_WEIGHTING
static final String PARAM_USE_SPARSE_FEATURES
static final String PARAM_REQUIRED_TYPES
static final String PARAM_ENFORCE_MATCHING_FEATURES
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