public class GIS extends Object
Modifier and Type | Field and Description |
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static boolean |
PRINT_MESSAGES
Set this to false if you don't want messages about the progress of model
training displayed.
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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.
|
Constructor and Description |
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GIS() |
Modifier and Type | Method and Description |
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static GISModel |
trainModel(EventStream eventStream)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(EventStream eventStream,
boolean smoothing)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(EventStream eventStream,
int iterations,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(EventStream eventStream,
int iterations,
int cutoff,
boolean smoothing,
boolean printMessagesWhileTraining)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(EventStream eventStream,
int iterations,
int cutoff,
double sigma)
Train a model using the GIS algorithm.
|
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.
|
public static boolean PRINT_MESSAGES
public static double SMOOTHING_OBSERVATION
public static GISModel trainModel(EventStream eventStream) throws IOException
eventStream
- The EventStream holding the data on which this model will be
trained.IOException
public static GISModel trainModel(EventStream eventStream, boolean smoothing) throws 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.IOException
public static GISModel trainModel(EventStream eventStream, int iterations, int cutoff) throws 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.IOException
public static GISModel trainModel(EventStream eventStream, int iterations, int cutoff, boolean smoothing, boolean printMessagesWhileTraining) throws 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.IOException
public static GISModel trainModel(EventStream eventStream, int iterations, int cutoff, double sigma) throws 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.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 © 2017 The Apache Software Foundation. All rights reserved.