Package | Description |
---|---|
org.tribuo |
Provides the core interfaces and classes for using Tribuo.
|
org.tribuo.hash |
Provides the base interface and implementations of the
Model hashing
which obscures the feature names stored in a model. |
org.tribuo.impl |
Provides implementations of base classes and interfaces from
org.tribuo . |
org.tribuo.sequence |
Provides core classes for working with sequences of
Example s. |
org.tribuo.transform |
Provides infrastructure for applying transformations to a
Dataset . |
Modifier and Type | Class and Description |
---|---|
class |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
class |
MutableFeatureMap
A feature map that can record new feature value observations.
|
Modifier and Type | Method and Description |
---|---|
abstract FeatureMap |
Dataset.getFeatureMap()
Returns this dataset's
FeatureMap . |
Modifier and Type | Method and Description |
---|---|
abstract void |
Example.canonicalize(FeatureMap featureMap)
Reassigns feature name Strings in the Example to point to those in the
FeatureMap . |
protected void |
Example.densify(FeatureMap fMap)
Converts all implicit zeros into explicit zeros based on the supplied feature map.
|
static Map<String,VariableIDInfo> |
ImmutableFeatureMap.generateIDs(FeatureMap map)
Generates the feature ids by sorting the features with the String comparator,
then sequentially numbering them.
|
Constructor and Description |
---|
FeatureMap(FeatureMap map)
Constructs a deep copy of the supplied feature map.
|
ImmutableDataset(DataSource<T> dataSource,
FeatureMap featureIDMap,
OutputInfo<T> outputIDInfo,
boolean dropInvalidExamples)
Creates a dataset from a data source.
|
ImmutableDataset(Iterable<Example<T>> dataSource,
DataProvenance description,
OutputFactory<T> outputFactory,
FeatureMap featureIDMap,
OutputInfo<T> outputIDInfo,
boolean dropInvalidExamples)
Creates a dataset from a data source.
|
ImmutableFeatureMap(FeatureMap map)
Constructs a new immutable version which is a deep copy of the supplied feature map, generating new ID numbers.
|
Modifier and Type | Class and Description |
---|---|
class |
HashedFeatureMap
A
FeatureMap used by the HashingTrainer to
provide feature name hashing and guarantee that the Model
does not contain feature name information, but still works
with unhashed features names. |
Modifier and Type | Method and Description |
---|---|
static HashedFeatureMap |
HashedFeatureMap.generateHashedFeatureMap(FeatureMap map,
Hasher hasher)
Converts a standard
FeatureMap by hashing each entry
using the supplied hash function Hasher . |
Modifier and Type | Method and Description |
---|---|
void |
ListExample.canonicalize(FeatureMap featureMap) |
void |
BinaryFeaturesExample.canonicalize(FeatureMap featureMap) |
void |
ArrayExample.canonicalize(FeatureMap featureMap) |
protected void |
BinaryFeaturesExample.densify(FeatureMap fMap) |
Modifier and Type | Method and Description |
---|---|
abstract FeatureMap |
SequenceDataset.getFeatureMap()
The feature map.
|
Modifier and Type | Method and Description |
---|---|
void |
SequenceExample.canonicalise(FeatureMap featureMap)
Reassigns feature name Strings in each Example inside this SequenceExample to point to
those in the
FeatureMap . |
Constructor and Description |
---|
ImmutableSequenceDataset(Iterable<SequenceExample<T>> dataSource,
DataProvenance sourceProvenance,
FeatureMap featureIDMap,
OutputInfo<T> outputIDInfo,
OutputFactory<T> outputFactory)
Creates a dataset from a data source.
|
ImmutableSequenceDataset(SequenceDataSource<T> dataSource,
FeatureMap featureIDMap,
OutputInfo<T> outputIDInfo) |
Modifier and Type | Method and Description |
---|---|
boolean |
TransformationMap.validateTransformations(FeatureMap featureMap)
Checks that a given transformation set doesn't have conflicts when applied to the supplied featureMap.
|
Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.