com.groiss.ml.ds

Interface DataSet

public interface DataSet

Interface representing a list of instances used for learning and/or evaluation. A data set also has to have attributes represented as Attribute objects.

Method Summary

Modifier and Type	Method and Description
boolean	add(Instance instance) Adds a new Instance to this data set
<T> List<Attribute<T>>	attributes() Returns the list of all attributes (inputs and output) of this data set.
DataSet	filtered(Predicate<Instance> filter) Returns a data set containing only the instances of this data set which fulfill the passed filter.
Iterable<Instance>	instances() Returns an Iterable with this data set as its source.
boolean	isEmpty() Returns true if this data set contains no instances.
<T> Attribute<T>	outputAttribute() Get the output attribute of the attributes of this DataSet, i.e. the attribute which predictions shall be learned.
boolean	remove(Instance instance) Removes an Instance from this data set
void	shuffle(Random random) Randomly permute the entries of this data set using the specified source of randomness.
int	size() Returns the number of instances in this data set.
TrainTestSets	split(double fraction) Splits the set of instances into a set for training and a set for testing according to the passed fraction.
TrainTestSets	split(int numFolds, int testIndex) Splits the set of instances into a set for training and a set for testing according to the passed number of folds and the index determining which one shall be used for testing.
Stream<Instance>	stream() Returns a sequential Stream with this data set as its source.

Method Detail

outputAttribute

<T> Attribute<T> outputAttribute()

Get the output attribute of the attributes of this DataSet, i.e. the attribute which predictions shall be learned.

Returns:

the Attribute representing the output attribute of this data set

attributes

<T> List<Attribute<T>> attributes()

Returns the list of all attributes (inputs and output) of this data set.

Returns:

a list of Attribute of this DataSet object

add

boolean add(Instance instance)

Adds a new Instance to this data set

Parameters:

instance - the instance to add

Returns:

true if this data set changed as a result of the call

remove

boolean remove(Instance instance)

Removes an Instance from this data set

Parameters:

instance - the instance to remove

Returns:

true if the instance was removed, false otherwise

size

int size()

Returns the number of instances in this data set.

Returns:

the number of instances in this data set

isEmpty

boolean isEmpty()

Returns true if this data set contains no instances.

Returns:

true if this data set contains no instances

instances

Iterable<Instance> instances()

Returns an Iterable with this data set as its source.

Returns:

an Iterable of Instances

stream

Stream<Instance> stream()

Returns a sequential Stream with this data set as its source.

Returns:

a Stream of Instances

shuffle

void shuffle(Random random)

Randomly permute the entries of this data set using the specified source of randomness.

Parameters:

random - the source of randomness to use to shuffle the entries

split

TrainTestSets split(double fraction)

Splits the set of instances into a set for training and a set for testing according to the passed fraction.

Parameters:

fraction - the fraction for the training set, the rest will be add to the test set.

Returns:

a TrainTestSets of train and test data

split

TrainTestSets split(int numFolds,
                    int testIndex)

Splits the set of instances into a set for training and a set for testing according to the passed number of folds and the index determining which one shall be used for testing.

Parameters:

numFolds - number of folds to apply to data set

testIndex - represents which part is used for testing

Returns:

a TrainTestSets of train and test data.

filtered

DataSet filtered(Predicate<Instance> filter)

Returns a data set containing only the instances of this data set which fulfill the passed filter.

Parameters:

filter - the predicate which must be fulfilled by a given instance to be part of the result

Returns:

a filtered data set