Package | Description |
---|---|
org.tribuo |
Provides the core interfaces and classes for using Tribuo.
|
org.tribuo.data.columnar |
Provides classes for processing columnar data and generating
Example s. |
org.tribuo.data.csv |
Provides classes which can load columnar data (using a
RowProcessor )
from a CSV (or other character delimited format) file. |
org.tribuo.data.sql |
Provides classes which can load columnar data (using a
RowProcessor )
from a SQL source. |
org.tribuo.data.text | |
org.tribuo.data.text.impl |
Provides implementations of text data processors.
|
org.tribuo.datasource |
Simple data sources for ingesting or aggregating data.
|
org.tribuo.evaluation |
Evaluation base classes, along with code for train/test splits and cross validation.
|
org.tribuo.json |
Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
|
org.tribuo.regression.example |
Provides some example regression data generators for testing implementations.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ConfigurableDataSource<T extends Output<T>>
It's a
DataSource that's also Configurable . |
Constructor and Description |
---|
Dataset(DataSource<T> dataSource)
Creates a dataset.
|
ImmutableDataset(DataSource<T> dataSource,
FeatureMap featureIDMap,
OutputInfo<T> outputIDInfo,
boolean dropInvalidExamples)
Creates a dataset from a data source.
|
ImmutableDataset(DataSource<T> dataSource,
Model<T> model,
boolean dropInvalidExamples)
Creates a dataset from a data source.
|
MutableDataset(DataSource<T> dataSource)
Creates a dataset from a data source.
|
Modifier and Type | Class and Description |
---|---|
class |
ColumnarDataSource<T extends Output<T>>
A
ConfigurableDataSource base class which takes columnar data (e.g., csv or DB table rows) and generates Example s. |
Modifier and Type | Class and Description |
---|---|
class |
CSVDataSource<T extends Output<T>>
A
DataSource for loading separable data from a text file (e.g., CSV, TSV)
and applying FieldProcessor s to it. |
Modifier and Type | Class and Description |
---|---|
class |
SQLDataSource<T extends Output<T>>
A
DataSource for loading columnar data from a database
and applying FieldProcessor s to it. |
Modifier and Type | Class and Description |
---|---|
class |
DirectoryFileSource<T extends Output<T>>
A data source for a somewhat-common format for text classification datasets:
a top level directory that contains a number of subdirectories.
|
class |
TextDataSource<T extends Output<T>>
A base class for textual data sets.
|
Modifier and Type | Class and Description |
---|---|
class |
SimpleStringDataSource<T extends Output<T>>
A version of
SimpleTextDataSource that accepts an Iterable of Strings. |
class |
SimpleTextDataSource<T extends Output<T>>
A dataset for a simple data format for text classification experiments.
|
Modifier and Type | Class and Description |
---|---|
class |
AggregateDataSource<T extends Output<T>>
Aggregates multiple
DataSource s, and round-robins the iterators. |
class |
IDXDataSource<T extends Output<T>>
A DataSource which can read IDX formatted data (i.e., MNIST).
|
class |
LibSVMDataSource<T extends Output<T>>
A DataSource which can read LibSVM formatted data.
|
class |
ListDataSource<T extends Output<T>>
A data source which wraps up a list of
Example s
along with their DataSourceProvenance and an OutputFactory . |
Constructor and Description |
---|
AggregateDataSource(List<DataSource<T>> sources) |
Modifier and Type | Method and Description |
---|---|
DataSource<T> |
TrainTestSplitter.getTest()
Gets the testing datasource.
|
DataSource<T> |
TrainTestSplitter.getTrain()
Gets the training data source.
|
Modifier and Type | Method and Description |
---|---|
E |
Evaluator.evaluate(Model<T> model,
DataSource<T> datasource)
Evaluates the dataset using the supplied model, returning an immutable
Evaluation of the appropriate type. |
E |
AbstractEvaluator.evaluate(Model<T> model,
DataSource<T> datasource)
Produces an evaluation for the supplied model and datasource, by calling
Model.predict(org.tribuo.Example<T>)
to create the predictions, then aggregating the appropriate statistics. |
Constructor and Description |
---|
TrainTestSplitter(DataSource<T> data)
Creates a splitter that splits a dataset 70/30 train and test using a default seed.
|
TrainTestSplitter(DataSource<T> data,
double trainProportion,
long seed)
Creates a splitter that will split the given data set into
a training and testing set.
|
TrainTestSplitter(DataSource<T> data,
long seed)
Creates a splitter that splits a dataset 70/30 train and test.
|
Modifier and Type | Class and Description |
---|---|
class |
JsonDataSource<T extends Output<T>>
A
DataSource for loading data from a JSON text file
and applying FieldProcessor s to it. |
Modifier and Type | Class and Description |
---|---|
class |
GaussianDataSource
Generates a single dimensional output drawn from N(slope*x + intercept,variance).
|
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