public class NBClassifierThread
extends java.lang.Thread
Constructor and Description |
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NBClassifierThread(WorkoutActivity activity,
ClassificationFeatures classificationFeatures,
weka.classifiers.Classifier model,
weka.core.Instances trainingSet)
Creates new NBClassifierThread, which uses the Naive Bayes algorithm
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Modifier and Type | Method and Description |
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static weka.core.FastVector |
getAttributes() |
static weka.core.Instance |
getInstanceFromClassificationFeatures(ClassificationFeatures classificationFeatures) |
void |
run() |
activeCount, checkAccess, countStackFrames, currentThread, destroy, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, stop, suspend, toString, yield
public NBClassifierThread(WorkoutActivity activity, ClassificationFeatures classificationFeatures, weka.classifiers.Classifier model, weka.core.Instances trainingSet)
activity
- WorkoutActivity, which gets updated with the classification resultsclassificationFeatures
- The latest computed features, which are used for classificationmodel
- Contains a Naive Bayes model, trained with a training settrainingSet
- The training set used for evaluationpublic void run()
run
in interface java.lang.Runnable
run
in class java.lang.Thread
public static weka.core.Instance getInstanceFromClassificationFeatures(ClassificationFeatures classificationFeatures)
public static weka.core.FastVector getAttributes()