Package 'LibOPF' reference manual

Title:	Design of Optimum-Path Forest Classifiers
Description:	The 'LibOPF' is a framework to develop pattern recognition techniques based on optimum-path forests (OPF), João P. Papa and Alexandre X. Falcão (2008) <doi:10.1007/978-3-540-89639-5_89>, with methods for supervised learning and data clustering.
Authors:	Rafael Junqueira Martarelli [aut, cre], João Paulo Papa [aut], Alexandre Xavier Falcão [cph]
Maintainer:	Rafael Junqueira Martarelli <[email protected]>
License:	BSD_2_clause + file LICENSE
Version:	2.6.0
Built:	2024-11-06 03:40:10 UTC
Source:	https://github.com/rafaeljm/libopf-in-r

Computes the OPF accuracy

Description

Computes the OPF accuracy

Usage

opf_accuracy(dataSet, classification)
opf_accuracy(dataSet, classification)

Arguments

`dataSet`	Data object used in the opf_classify function (subGraph object), normaly is the testing object
`classification`	The output list produced by opf_classify function

Value

Returns the classification accuracy

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Computes the OPF accuracy for each class of a given set

Description

Computes the OPF accuracy for each class of a given set

Usage

opf_accuracy4label(dataSet, classification)
opf_accuracy4label(dataSet, classification)

Arguments

`dataSet`	Data object used in in the opf_classify function (subGraph object), normaly is the testing object
`classification`	The output list produced by opf_classify function

Value

Returns the classification accuracy for each class

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy4label(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy4label(T2, class)

Checks the OPF file for proper formatting purposes

Description

Checks the OPF file for proper formatting purposes

Usage

opf_check(file)
opf_check(file)

Arguments

file

The text OPF file name

Details

usage opf_check <input ASCII file in the LibOPF format>: Note that the input file for opf_check must be a text file. Use opf2txt to convert your OPF binary file into a text file.

Value

'NULL'

Examples

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.txt")
opf2txt(dataset,File)
opf_check(File)

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.txt")
opf2txt(dataset,File)
opf_check(File)

Executes the test phase of the OPF classifier

Description

Executes the test phase of the OPF classifier

Usage

opf_classify(dataSet, classifier, precomputedDistance = NA)
opf_classify(dataSet, classifier, precomputedDistance = NA)

Arguments

`dataSet`	The testing data object produced by the opf_split function (subGraph object)
`classifier`	The classifier object produced by one of the classification functions (model object)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Value

Returns the given subGraph classification list (predicted labels)

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Computes clusters by unsupervised OPF

Description

Computes clusters by unsupervised OPF

Usage

opf_cluster(dataSet, kmax, calculateOp, value, precomputedDistance = NA)
opf_cluster(dataSet, kmax, calculateOp, value, precomputedDistance = NA)

Arguments

`dataSet`	The training object produced by the opf_split function (subGraph object)
`kmax`	The kmax (maximum degree for the knn graph)
`calculateOp`	Clusters by: 0 for height, 1 for area and 2 for volume
`value`	Value of parameter "calculateOp" in [0-1]
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Value

Returns a list which contains the classifier object and the classification list object (i.e., clusters' id)

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.8,0,0.2,0)
T <- X$training
T2 <- X$testing
Y <- opf_cluster(T,100,1,0.2)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.8,0,0.2,0)
T <- X$training
T2 <- X$testing
Y <- opf_cluster(T,100,1,0.2)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Creates an empty subGraph structure

Description

Creates an empty subGraph structure

Usage

opf_create_subGraph(nnodes)
opf_create_subGraph(nnodes)

Arguments

nnodes

Number of nodes

Value

Returns an empty subGraph

Examples

EmptySubgraph <- opf_create_subGraph(10)

EmptySubgraph <- opf_create_subGraph(10)

Generates the precomputed distance file for the OPF classifier

Description

Generates the precomputed distance file for the OPF classifier

Usage

opf_distance(dataSet, distanceOp, normalize = 0)
opf_distance(dataSet, distanceOp, normalize = 0)

Arguments

`dataSet`	The subGraph object, normaly is the whole data
`distanceOp`	Distance calculation option
`normalize`	Distance normalization? 1- yes 0 - no

Details

Options for distance calculation:
1 - Euclidean
2 - Chi-Square
3 - Manhattan (L1)
4 - Canberra
5 - Squared Chord
6 - Squared Chi-Squared
7 - BrayCurtis

Value

Returns the distance matrix

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dist <- opf_distance(dat,3,0)
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T,dist)
class <- opf_classify(T2, Y$classifier,dist)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dist <- opf_distance(dat,3,0)
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T,dist)
class <- opf_classify(T2, Y$classifier,dist)
acc <- opf_accuracy(T2, class)

Generates k folds (objects) for the OPF classifier

Description

Generates k folds (objects) for the OPF classifier

Usage

opf_fold(dataSet, k, normalize = 0)
opf_fold(dataSet, k, normalize = 0)

Arguments

`dataSet`	The subGraph object
`k`	Number of folds
`normalize`	Distance normalization? 1- yes 0 - no

Value

Returns a list of subGraph objects

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
folds <- opf_fold(dat, 4)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
folds <- opf_fold(dat, 4)

Gives information about the OPF file

Description

Gives information about the OPF file

Usage

opf_info(dataSet)
opf_info(dataSet)

Arguments

dataSet

The OPF file

Value

'NULL'

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
opf_info(dat)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
opf_info(dat)

Executes the test phase of the OPF classifier with knn adjacency

Description

Executes the test phase of the OPF classifier with knn adjacency

Usage

opf_knn_classify(dataSet, classifier, precomputedDistance = NA)
opf_knn_classify(dataSet, classifier, precomputedDistance = NA)

Arguments

`dataSet`	The testing object produced by the opf_split (subGraph object)
`classifier`	The classifier object produced by one of the classification functions (model object)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Value

Returns the given subGraph classification list

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.8,0,0.2,0)
T <- X$training
T2 <- X$testing
Y <- opf_cluster(T,100,1,0.2)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.8,0,0.2,0)
T <- X$training
T2 <- X$testing
Y <- opf_cluster(T,100,1,0.2)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Executes the training phase of the OPF classifier with knn adjacency

Description

Executes the training phase of the OPF classifier with knn adjacency

Usage

opf_knn_train(trainFile, evaluatFile, kmax, precomputedDistance = NA)
opf_knn_train(trainFile, evaluatFile, kmax, precomputedDistance = NA)

Arguments

`trainFile`	The training object produced by the opf_split (subGraph object)
`evaluatFile`	The evaluation object produced by the opf_split (subGraph object)
`kmax`	The kmax (maximum degree for the knn graph)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Details

Returns a list which contains the classifier object and the classification list object

Value

Returns a list which contains the classifier object and the classification list object (i.e., clusters' id)

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_knn_train(T,E,100)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_knn_train(T,E,100)
class <- opf_knn_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Executes the learning phase of the OPF classifier

Description

Executes the learning phase of the OPF classifier

Usage

opf_learn(trainFile, evaluatFile, precomputedDistance = NA)
opf_learn(trainFile, evaluatFile, precomputedDistance = NA)

Arguments

`trainFile`	The training object produced by the opf_split (subGraph object)
`evaluatFile`	The evaluation produced object by the opf_split (subGraph object)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Details

Executes the training phase

Value

Returns a list which contains the classifier model object

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_learn(T,E)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_learn(T,E)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Merge subGraphs

Description

Merge subGraphs

Usage

opf_merge(dataSets)
opf_merge(dataSets)

Arguments

dataSets

An array of subGraph objects

Value

Returns the merged subGraph object

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dat2 <- opf_read_subGraph(system.file("extdata/Z1LINE.dat",package = "LibOPF"))
dataSet <- opf_merge(c(dat,dat2))

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dat2 <- opf_read_subGraph(system.file("extdata/Z1LINE.dat",package = "LibOPF"))
dataSet <- opf_merge(c(dat,dat2))

Normalizes data for the OPF classifier

Description

Normalizes data for the OPF classifier

Usage

opf_normalize(dataSet)
opf_normalize(dataSet)

Arguments

dataSet

The subGraph object

Value

Returns the normalized subGraph

Examples

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dat <- opf_normalize(dataset)

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dat <- opf_normalize(dataset)

Executes the pruning algorithm

Description

Executes the pruning algorithm

Usage

opf_pruning(
  dataTraining,
  dataEvaluating,
  percentageAccuracy,
  precomputedDistance = NA
)
opf_pruning(
  dataTraining,
  dataEvaluating,
  percentageAccuracy,
  precomputedDistance = NA
)

Arguments

`dataTraining`	The training object produced by the opf_split (subGraph object)
`dataEvaluating`	The evaluating object produced by the opf_split (subGraph object)
`percentageAccuracy`	Max percentage of lost accuracy [0,1]
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Value

Returns a list which contains the classifier model object

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_pruning(T,E,0.8)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.3,0.2,0.5,0)
T <- X$training
T2 <- X$testing
E <- X$evaluating
Y <- opf_pruning(T,E,0.8)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Reads a file which contains the nodes' predicted labels

Description

Reads a file which contains the nodes' predicted labels

Usage

opf_read_classification(file)
opf_read_classification(file)

Arguments

file

The file which contains the nodes' predicted labels

Value

Returns the predicted labels list

Examples

File <- system.file("extdata/classification.txt",package = "LibOPF")
classification <- opf_read_classification(File)

File <- system.file("extdata/classification.txt",package = "LibOPF")
classification <- opf_read_classification(File)

Reads a file which contains the precalculated distances

Description

Reads a file which contains the precalculated distances

Usage

opf_read_distances(file)
opf_read_distances(file)

Arguments

file

The file which contains the distances matrix

Value

Returns the precalculated distances matrix

Examples

distances <- opf_read_distances(system.file("extdata/distances.dat",package = "LibOPF"))

distances <- opf_read_distances(system.file("extdata/distances.dat",package = "LibOPF"))

Reads a file which contains the learned model

Description

Reads a file which contains the learned model

Usage

opf_read_modelfile(file)
opf_read_modelfile(file)

Arguments

file

The file which contains the learned model

Value

Returns the learned model object

Examples

classifier <- opf_read_modelfile(system.file("extdata/classifier.opf",package = "LibOPF"))

classifier <- opf_read_modelfile(system.file("extdata/classifier.opf",package = "LibOPF"))

Reads a file which contains the subGraph

Description

Reads a file which contains the subGraph

Usage

opf_read_subGraph(file)
opf_read_subGraph(file)

Arguments

file

The file name

Value

Returns the subGraph object

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(dataset) (dataset is the subgraph file)
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Usage

opf_run_example(dataset)
opf_run_example(dataset)

Arguments

dataset

A dataset folder for the test

Value

Returns the accuracy

Executes the semi supervised training phase

Description

Executes the semi supervised training phase

Usage

opf_semi(
  labeledTrainSubGraph,
  unLabeledTrainSubGraph,
  evaluatFile = NA,
  precomputedDistance = NA
)
opf_semi(
  labeledTrainSubGraph,
  unLabeledTrainSubGraph,
  evaluatFile = NA,
  precomputedDistance = NA
)

Arguments

`labeledTrainSubGraph`	The labeled training object (subGraph object)
`unLabeledTrainSubGraph`	The unlabeled training object (subGraph object)
`evaluatFile`	The evaluation object produced by the opf_split (subGraph object)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Details

Returns the learned model object

Value

Returns a list which contains the classifier object and the classification list object

Examples

Training <- opf_read_subGraph(system.file("extdata/Z1LINE.dat",package = "LibOPF"))
TUnlabeled <- opf_read_subGraph(system.file("extdata/Z1DOUBLELINE.dat",package = "LibOPF"))
Testing <- opf_read_subGraph(system.file("extdata/Z3.dat",package = "LibOPF"))
Y <- opf_semi(Training,TUnlabeled)
class <- opf_classify(Testing, Y$classifier)
acc <- opf_accuracy(Testing, class)

Training <- opf_read_subGraph(system.file("extdata/Z1LINE.dat",package = "LibOPF"))
TUnlabeled <- opf_read_subGraph(system.file("extdata/Z1DOUBLELINE.dat",package = "LibOPF"))
Testing <- opf_read_subGraph(system.file("extdata/Z3.dat",package = "LibOPF"))
Y <- opf_semi(Training,TUnlabeled)
class <- opf_classify(Testing, Y$classifier)
acc <- opf_accuracy(Testing, class)

Generates training, evaluation and test sets for the OPF classifier

Description

Generates training, evaluation and test sets for the OPF classifier

Usage

opf_split(dataSet, training_p, evaluating_p, testing_p, normalize = 0)
opf_split(dataSet, training_p, evaluating_p, testing_p, normalize = 0)

Arguments

`dataSet`	The data (subGraph object)
`training_p`	Percentage for the training set size [0,1]
`evaluating_p`	Percentage for the evaluation set size [0,1] (leave 0 in the case of no learning)
`testing_p`	Percentage for the test set size [0,1]
`normalize`	Distance normalization? 1- yes 0 - no

Value

Returns the training, evaluating and the testing objects

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Executes the training phase of the OPF classifier

Description

Executes the training phase of the OPF classifier

Usage

opf_train(dataSet, precomputedDistance = NA)
opf_train(dataSet, precomputedDistance = NA)

Arguments

`dataSet`	The training object produced by the opf_split (subGraph object)
`precomputedDistance`	The precomputed distance matrix produced by the opf_distance (leave it in blank if you are not using this resource)

Value

Returns a list which contains the classifier object and the classification list object

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
class <- opf_classify(T2, Y$classifier)
acc <- opf_accuracy(T2, class)

Writes into a file the predicted labels produced by the opf classificator

Description

Writes into a file the predicted labels produced by the opf classificator

Usage

opf_write_classification(classes, file)
opf_write_classification(classes, file)

Arguments

`classes`	The classification list (i.e.,predicted labels) produced by the classifier
`file`	Where you want to save the classification vector

Value

'NULL'

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
opf_write_classification(Y$classification, file.path(tempdir(), "classification.txt"))

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
opf_write_classification(Y$classification, file.path(tempdir(), "classification.txt"))

Writes into a file the precalculated distances computed by opf_distances function

Description

Writes into a file the precalculated distances computed by opf_distances function

Usage

opf_write_distances(distances, file)
opf_write_distances(distances, file)

Arguments

`distances`	The matrix produced by the opf distances function
`file`	The file name where you want to save the distances

Value

'NULL'

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dist <- opf_distance(dat,3,0)
opf_write_distances(dist, file.path(tempdir(), "distances.dat"))

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
dist <- opf_distance(dat,3,0)
opf_write_distances(dist, file.path(tempdir(), "distances.dat"))

Writes into a file the trained OPF classifier

Description

Writes into a file the trained OPF classifier

Usage

opf_write_modelfile(g, file)
opf_write_modelfile(g, file)

Arguments

`g`	The classifier object
`file`	The file name to save the classifier

Value

'NULL'

Examples

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
opf_write_modelfile(Y$classifier, file.path(tempdir(), "classifier.opf"))

dat <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
X <- opf_split(dat,0.5,0,0.5,0)
T <- X$training
T2 <- X$testing
Y <- opf_train(T)
opf_write_modelfile(Y$classifier, file.path(tempdir(), "classifier.opf"))

Writes into a file a subGraph

Description

Writes into a file a subGraph

Usage

opf_write_subGraph(g, file)
opf_write_subGraph(g, file)

Arguments

`g`	The subGraph object
`file`	The file name to save the subGraph

Value

'NULL'

Examples

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
opf_write_subGraph(dataset, file.path(tempdir(), "boat.dat"))

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
opf_write_subGraph(dataset, file.path(tempdir(), "boat.dat"))

Converts an OPF subGraph object to a LIBSVM file

Description

Converts an OPF subGraph object to a LIBSVM file

Usage

opf2svm(data, outputFile)
opf2svm(data, outputFile)

Arguments

`data`	The subGraph object
`outputFile`	LIBSVM output file name

Value

'NULL'

Examples

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.svm")
opf2svm(dataset,File)
opf_check(File)

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.svm")
opf2svm(dataset,File)
opf_check(File)

Converts an OPF subGraph object to a text file

Description

Converts an OPF subGraph object to a text file

Usage

opf2txt(data, outputFile)
opf2txt(data, outputFile)

Arguments

`data`	OPF subGraph object
`outputFile`	Text output file name

Value

'NULL'

Examples

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.txt")
opf2txt(dataset,File)

dataset <- opf_read_subGraph(system.file("extdata/boat.dat",package = "LibOPF"))
File <- file.path(tempdir(), "boat.txt")
opf2txt(dataset,File)

Subgraphs' node class

Description

Subgraphs' node class

Subgraph class

Description

Subgraph class

Converts a LIBSVM file to an OPF subGraph object

Description

Converts a LIBSVM file to an OPF subGraph object

Usage

svm2opf(inputFile)
svm2opf(inputFile)

Arguments

inputFile

LIBSVM input file

Value

Returns the OPF object

Examples

dataset <- svm2opf(system.file("extdata/boat.svm",package = "LibOPF"))

dataset <- svm2opf(system.file("extdata/boat.svm",package = "LibOPF"))

Converts a text file to an OPF subGraph object

Description

Converts a text file to an OPF subGraph object

Usage

txt2opf(inputFile)
txt2opf(inputFile)

Arguments

inputFile

Text input file

Value

Returns the OPF object

Examples

dataset <- txt2opf(system.file("extdata/boat.txt",package = "LibOPF"))

dataset <- txt2opf(system.file("extdata/boat.txt",package = "LibOPF"))

Package 'LibOPF'

Help Index

Computes the OPF accuracy

Description

Usage

Arguments

Value

Examples

Computes the OPF accuracy for each class of a given set

Description

Usage

Arguments

Value

Examples

Checks the OPF file for proper formatting purposes

Description

Usage

Arguments

Details

Value

Examples

Executes the test phase of the OPF classifier

Description

Usage

Arguments

Value

Examples

Computes clusters by unsupervised OPF

Description

Usage

Arguments

Value

Examples

Creates an empty subGraph structure

Description

Usage

Arguments

Value

Examples

Generates the precomputed distance file for the OPF classifier

Description

Usage

Arguments

Details

Value

Examples

Generates k folds (objects) for the OPF classifier

Description

Usage

Arguments

Value

Examples

Gives information about the OPF file

Description

Usage

Arguments

Value

Examples

Executes the test phase of the OPF classifier with knn adjacency

Description

Usage

Arguments

Value

Examples

Executes the training phase of the OPF classifier with knn adjacency

Description

Usage

Arguments

Details

Value

Examples

Executes the learning phase of the OPF classifier

Description

Usage

Arguments

Details

Value

Examples

Merge subGraphs

Description