/usr/include/openturns/swig/ClassifierImplementation_doc.i is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 | %define OT_Classifier_doc
"Classifier.
Available constructors:
Classifier(*classifierImp*)
Parameters
----------
classifierImp : classifier implementation
A classifier implementation. It can be a :class:`~openturns.MixtureClassifier`.
See also
--------
MixtureClassifier, ExpertMixture
Notes
-----
The classifier enables to define rules that assign a vector to a particular
class."
%enddef
%feature("docstring") OT::ClassifierImplementation
OT_Classifier_doc
// ---------------------------------------------------------------------
%define OT_Classifier_classify_doc
"Classify points according to the classifier.
**Available usages**:
classify(*inputPoint*)
classify(*inputSample*)
Parameters
----------
inputPoint : sequence of float
A point to classify.
inputSample : 2-d a sequence of float
A set of point to classify.
Notes
-----
The rules to assign a point to a class are specific to each *classifierImp*.
In the first usage, it returns an integer which corresponds to the class where
*inputPoint* has been assigned.
In the second usage, it returns an :class:`~openturns.Indices` that collects the
class of each point of *inputSample*."
%enddef
%feature("docstring") OT::ClassifierImplementation::classify
OT_Classifier_classify_doc
// ---------------------------------------------------------------------
%define OT_Classifier_grade_doc
"Grade points according to the classifier.
**Available usages**:
grade(*inputPoint, k*)
grade(*inputSample, classList*)
Parameters
----------
inputPoint : sequence of float
A point to grade.
inputSample : 2-d a sequence of float
A set of point to grade.
k : integer
The class number.
classList : sequence of integer
The list of class number.
Notes
-----
The rules to grade a point with respect to a class are specific to each
*classifierImp*.
In the first usage, it returns a real that grades *inputPoint* with respect to
the class *k*. The greatest, the best.
In the second usage, it returns an :class:`~openturns.Indices` that collects the
grades of the :math:`i^{th}` point of *inputSample* with respect to the
:math:`i^{th}` class of *classList*."
%enddef
%feature("docstring") OT::ClassifierImplementation::grade
OT_Classifier_grade_doc
// ---------------------------------------------------------------------
%define OT_Classifier_getDimension_doc
"Accessor to the dimension.
Returns
-------
dim : integer
The dimension of the classifier."
%enddef
%feature("docstring") OT::ClassifierImplementation::getDimension
OT_Classifier_getDimension_doc
// ---------------------------------------------------------------------
%define OT_Classifier_getVerbose_doc
"Accessor to the verbosity.
Returns
-------
verb : bool
Logical value telling if the verbose mode has been activated."
%enddef
%feature("docstring") OT::ClassifierImplementation::getVerbose
OT_Classifier_getVerbose_doc
// ---------------------------------------------------------------------
%define OT_Classifier_setVerbose_doc
"Accessor to the verbosity.
Parameters
----------
verb : bool
Logical value telling if the verbose mode has been activated."
%enddef
%feature("docstring") OT::ClassifierImplementation::setVerbose
OT_Classifier_setVerbose_doc
// ---------------------------------------------------------------------
%define OT_Classifier_setParallel_doc
"Accessor to the parallel flag.
Parameters
----------
flag : bool
Logical value telling if the classification and grading are done in parallel.
"
%enddef
%feature("docstring") OT::ClassifierImplementation::setParallel
OT_Classifier_setParallel_doc
// ---------------------------------------------------------------------
%define OT_Classifier_isParallel_doc
"Accessor to the parallel flag.
Returns
-------
flag : bool
Logical value telling if the parallel mode has been activated.
"
%enddef
%feature("docstring") OT::ClassifierImplementation::isParallel
OT_Classifier_isParallel_doc
|