Modifier and Type | Method and Description |
---|---|
Instances |
DecisionTreeFunctionEstimator.getInstances() |
Modifier and Type | Method and Description |
---|---|
Instances |
AbstractDMNMiner.createTrainingSet(PossibleModel m) |
Modifier and Type | Method and Description |
---|---|
static org.apache.commons.math3.linear.RealMatrix |
CorrelationsCalculator.datToMat(Instances dat) |
Modifier and Type | Field and Description |
---|---|
protected Instances |
Evaluation.m_Header
The header of the training set.
|
Modifier and Type | Method and Description |
---|---|
Instances |
Evaluation.getHeader()
Returns the header of the underlying dataset.
|
Modifier and Type | Method and Description |
---|---|
void |
Evaluation.crossValidateModel(weka.classifiers.Classifier classifier,
Instances data,
int numFolds,
java.util.Random random,
java.lang.Object... forPredictionsPrinting)
Performs a (stratified if class is nominal) cross-validation for a
classifier on a set of instances.
|
void |
Evaluation.crossValidateModel(java.lang.String classifierString,
Instances data,
int numFolds,
java.lang.String[] options,
java.util.Random random)
Performs a (stratified if class is nominal) cross-validation for a
classifier on a set of instances.
|
double[] |
Evaluation.evaluateModel(weka.classifiers.Classifier classifier,
Instances data,
java.lang.Object... forPredictionsPrinting)
Evaluates the classifier on a given set of instances.
|
void |
Evaluation.setPriors(Instances train)
Sets the class prior probabilities.
|
Constructor and Description |
---|
Evaluation(Instances data)
Initializes all the counters for the evaluation.
|
Evaluation(Instances data,
weka.classifiers.CostMatrix costMatrix)
Initializes all the counters for the evaluation and also takes a cost
matrix as parameter.
|
Modifier and Type | Method and Description |
---|---|
static Instances |
Instances.mergeInstances(Instances first,
Instances second)
Merges two sets of Instances together.
|
Instances |
Instances.resample(java.util.Random random)
Creates a new dataset of the same size using random sampling with
replacement.
|
Instances |
Instances.resampleWithWeights(java.util.Random random)
Creates a new dataset of the same size using random sampling with
replacement according to the current instance weights.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
boolean representUsingWeights)
Creates a new dataset of the same size using random sampling with
replacement according to the current instance weights.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
boolean[] sampled)
Creates a new dataset of the same size using random sampling with
replacement according to the current instance weights.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
boolean[] sampled,
boolean representUsingWeights)
Creates a new dataset of the same size using random sampling with
replacement according to the current instance weights.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
double[] weights)
Creates a new dataset of the same size using random sampling with
replacement according to the given weight vector.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
double[] weights,
boolean[] sampled)
Creates a new dataset of the same size using random sampling with
replacement according to the given weight vector.
|
Instances |
Instances.resampleWithWeights(java.util.Random random,
double[] weights,
boolean[] sampled,
boolean representUsingWeights)
Creates a new dataset of the same size using random sampling with
replacement according to the given weight vector.
|
Instances |
Instances.stringFreeStructure()
Create a copy of the structure.
|
Instances |
Instances.testCV(int numFolds,
int numFold)
Creates the test set for one fold of a cross-validation on the dataset.
|
Instances |
Instances.trainCV(int numFolds,
int numFold)
Creates the training set for one fold of a cross-validation on the dataset.
|
Instances |
Instances.trainCV(int numFolds,
int numFold,
java.util.Random random)
Creates the training set for one fold of a cross-validation on the dataset.
|
Modifier and Type | Method and Description |
---|---|
protected void |
Instances.copyInstances(int from,
Instances dest,
int num)
Copies instances from one set to the end of another one.
|
boolean |
Instances.equalHeaders(Instances dataset)
Checks if two headers are equivalent.
|
java.lang.String |
Instances.equalHeadersMsg(Instances dataset)
Checks if two headers are equivalent.
|
protected void |
Instances.initialize(Instances dataset,
int capacity)
initializes with the header information of the given dataset and sets the
capacity of the set of instances.
|
static Instances |
Instances.mergeInstances(Instances first,
Instances second)
Merges two sets of Instances together.
|
Constructor and Description |
---|
Instances(Instances dataset)
Constructor copying all instances and references to the header information
from the given set of instances.
|
Instances(Instances dataset,
int capacity)
Constructor creating an empty set of instances.
|
Instances(Instances source,
int first,
int toCopy)
Creates a new set of instances by copying a subset of another set.
|