public class GIS extends AbstractEventTrainer
Modifier and Type | Field and Description |
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static java.lang.String |
MAXENT_VALUE |
static boolean |
PRINT_MESSAGES
Set this to false if you don't want messages about the progress of model
training displayed.
|
static double |
SMOOTHING_OBSERVATION
If we are using smoothing, this is used as the "number" of times we want
the trainer to imagine that it saw a feature that it actually didn't see.
|
DATA_INDEXER_ONE_PASS_VALUE, DATA_INDEXER_PARAM, DATA_INDEXER_TWO_PASS_VALUE
ALGORITHM_PARAM, CUTOFF_DEFAULT, CUTOFF_PARAM, ITERATIONS_DEFAULT, ITERATIONS_PARAM, TRAINER_TYPE_PARAM
EVENT_VALUE
Constructor and Description |
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GIS() |
Modifier and Type | Method and Description |
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AbstractModel |
doTrain(DataIndexer indexer) |
boolean |
isSortAndMerge() |
boolean |
isValid() |
static GISModel |
trainModel(int iterations,
DataIndexer indexer)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean smoothing)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff,
int threads)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
DataIndexer indexer,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm with the specified number of
iterations, data indexer, and prior.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
boolean smoothing)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff,
boolean smoothing,
boolean printMessagesWhileTraining)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(ObjectStream<Event> eventStream,
int iterations,
int cutoff,
double sigma)
Train a model using the GIS algorithm.
|
getDataIndexer, train
getAlgorithm, getCutoff, getIterations, init
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
init
public static final java.lang.String MAXENT_VALUE
public static boolean PRINT_MESSAGES
public static double SMOOTHING_OBSERVATION
public boolean isValid()
isValid
in class AbstractEventTrainer
public boolean isSortAndMerge()
isSortAndMerge
in class AbstractEventTrainer
public AbstractModel doTrain(DataIndexer indexer) throws java.io.IOException
doTrain
in class AbstractEventTrainer
java.io.IOException
public static GISModel trainModel(ObjectStream<Event> eventStream) throws java.io.IOException
eventStream
- The EventStream holding the data on which this model will be
trained.java.io.IOException
public static GISModel trainModel(ObjectStream<Event> eventStream, boolean smoothing) throws java.io.IOException
eventStream
- The EventStream holding the data on which this model will be
trained.smoothing
- Defines whether the created trainer will use smoothing while
training the model.java.io.IOException
public static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff) throws java.io.IOException
eventStream
- The EventStream holding the data on which this model will be
trained.iterations
- The number of GIS iterations to perform.cutoff
- The number of times a feature must be seen in order to be relevant
for training.java.io.IOException
public static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff, boolean smoothing, boolean printMessagesWhileTraining) throws java.io.IOException
eventStream
- The EventStream holding the data on which this model will be
trained.iterations
- The number of GIS iterations to perform.cutoff
- The number of times a feature must be seen in order to be relevant
for training.smoothing
- Defines whether the created trainer will use smoothing while
training the model.printMessagesWhileTraining
- Determines whether training status messages are written to STDOUT.java.io.IOException
public static GISModel trainModel(ObjectStream<Event> eventStream, int iterations, int cutoff, double sigma) throws java.io.IOException
eventStream
- The EventStream holding the data on which this model will be
trained.iterations
- The number of GIS iterations to perform.cutoff
- The number of times a feature must be seen in order to be relevant
for training.sigma
- The standard deviation for the gaussian smoother.java.io.IOException
public static GISModel trainModel(int iterations, DataIndexer indexer, boolean smoothing)
iterations
- The number of GIS iterations to perform.indexer
- The object which will be used for event compilation.smoothing
- Defines whether the created trainer will use smoothing while
training the model.public static GISModel trainModel(int iterations, DataIndexer indexer)
iterations
- The number of GIS iterations to perform.indexer
- The object which will be used for event compilation.public static GISModel trainModel(int iterations, DataIndexer indexer, Prior modelPrior, int cutoff)
iterations
- The number of GIS iterations to perform.indexer
- The object which will be used for event compilation.modelPrior
- The prior distribution for the model.public static GISModel trainModel(int iterations, DataIndexer indexer, boolean printMessagesWhileTraining, boolean smoothing, Prior modelPrior, int cutoff)
iterations
- The number of GIS iterations to perform.indexer
- The object which will be used for event compilation.printMessagesWhileTraining
- Determines whether training status messages are written to STDOUT.smoothing
- Defines whether the created trainer will use smoothing while
training the model.modelPrior
- The prior distribution for the model.cutoff
- The number of times a predicate must occur to be used in a model.public static GISModel trainModel(int iterations, DataIndexer indexer, boolean printMessagesWhileTraining, boolean smoothing, Prior modelPrior, int cutoff, int threads)
iterations
- The number of GIS iterations to perform.indexer
- The object which will be used for event compilation.printMessagesWhileTraining
- Determines whether training status messages are written to STDOUT.smoothing
- Defines whether the created trainer will use smoothing while
training the model.modelPrior
- The prior distribution for the model.cutoff
- The number of times a predicate must occur to be used in a model.Copyright © 2010 - 2020 Adobe. All Rights Reserved