pyplt.util package

Submodules

pyplt.util.enums module

This module contains a number of classes defining different types of enumerated constants used throughout PLT.

class pyplt.util.enums.ActivationType

Bases: enum.Enum

Class specifying enumerated constants for types of activation functions used by Backpropagation.

Extends enum.Enum.

LINEAR = 0
RELU = 2
SIGMOID = 1
class pyplt.util.enums.DataSetType

Bases: enum.Enum

Class specifying enumerated constants for types of ranks present in data sets.

Extends the class enum.Enum.

ORDERED = 2
PREFERENCES = 1
class pyplt.util.enums.EvaluatorType

Bases: enum.Enum

Class specifying enumerated constants for evaluators.

Extends enum.Enum.

HOLDOUT = 1
KFCV = 2
NONE = 0
class pyplt.util.enums.FSMethod

Bases: enum.Enum

Class specifying enumerated constants for feature selection methods.

Extends enum.Enum.

NONE = 0
N_BEST = 1
SBS = 3
SFS = 2
class pyplt.util.enums.FileType

Bases: enum.Enum

Class specifying enumerated constants for data file types.

Extends the class enum.Enum.

OBJECTS = 1
RANKS = 2
SINGLE = 3
class pyplt.util.enums.KernelType

Bases: enum.Enum

Class specifying enumerated constants for kernels used by RankSVM.

Extends enum.Enum.

LINEAR = 0
POLY = 2
RBF = 1
class pyplt.util.enums.NormalizationType

Bases: enum.Enum

Class specifying enumerated constants for data normalization methods.

Extends the class enum.Enum.

MIN_MAX = 1
NONE = 0
Z_SCORE = 2
class pyplt.util.enums.PLAlgo

Bases: enum.Enum

Class specifying enumerated constants for preference learning algorithms.

Extends enum.Enum.

BACKPROPAGATION = 2
BACKPROPAGATION_SKLEARN = 3
NEUROEVOLUTION = 4
RANKNET = 5
RANKSVM = 1
class pyplt.util.enums.ParamType

Bases: enum.Enum

Class specifying enumerated constants for parameter types.

Extends enum.Enum.

FLOAT = 1
FLOAT_POSITIVE = 2
INT = 0

Module contents

This package defines a number of utility classes for backend processes of PLT.

class pyplt.util.AbortFlag

Bases: object

This utility class assists the termination of experiments before completion.

Initializes a stopping flag variable to False (boolean).

The stopping variable indicates whether or not the experiment should be stopped.

stop()

Set the stopping flag to True.

stopped()

Get the stopping flag which indicates whether or not the experiment should be stopped.

Returns:the stopping flag.
Return type:bool