phynexis-deps/cgal
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Uniformize capital / third person usage of \brief

Browse Source
This commit is contained in:
Mael Rouxel-Labbé
2020-06-25 15:13:47 +02:00
parent d5d8cca92b
commit 26355e2e32
114 changed files with 448 additions and 448 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Classification/include/CGAL/Classification/Cluster.h
+9 -9
View File
@@ -122,7 +122,7 @@ public:
void clear () { m_inliers->clear(); }
/*!
\brief Inserts element of index `idx` in the cluster.
\brief inserts element of index `idx` in the cluster.
*/
void insert (std::size_t idx) { m_inliers->push_back (idx); }
@@ -132,23 +132,23 @@ public:
/// @{
/*!
\brief Returns the number of items in the cluster.
\brief returns the number of items in the cluster.
*/
std::size_t size() const { return m_inliers->size(); }
/*!
\brief Returns the index (in the input range) of the i^{th} element of the cluster.
\brief returns the index (in the input range) of the i^{th} element of the cluster.
*/
std::size_t index (std::size_t i) const { return (*m_inliers)[i]; }
/*!
\brief Returns the i^{th} item of the cluster.
\brief returns the i^{th} item of the cluster.
*/
const Item& operator[] (std::size_t i) const
{ return get (m_item_map, *(m_range->begin() + (*m_inliers)[i])); }
/*!
\brief Returns the bounding box of the cluster.
\brief returns the bounding box of the cluster.
*/
const CGAL::Bbox_3& bbox() const
{
@@ -168,22 +168,22 @@ public:
/// @{
/*!
\brief Returns the input classification value used for training.
\brief returns the input classification value used for training.
*/
int training() const { return m_training; }
/*!
\brief Returns a reference to the input classification value used for training.
\brief returns a reference to the input classification value used for training.
*/
int& training() { return m_training; }
/*!
\brief Returns the output classification value.
\brief returns the output classification value.
*/
int label() const { return m_label; }
/*!
\brief Returns a reference to the output classification value.
\brief returns a reference to the output classification value.
*/
int& label() { return m_label; }
Classification/include/CGAL/Classification/ETHZ/Random_forest_classifier.h
+4 -4
View File
@@ -81,7 +81,7 @@ public:
/// @{
/*!
\brief Instantiates the classifier using the sets of `labels` and `features`.
\brief instantiates the classifier using the sets of `labels` and `features`.
*/
Random_forest_classifier (const Label_set& labels,
@@ -138,7 +138,7 @@ public:
/// \endcond
/*!
\brief Runs the training algorithm.
\brief runs the training algorithm.
From the set of provided ground truth, this algorithm estimates
sets up the random trees that produce the most accurate result
@@ -280,7 +280,7 @@ public:
/// @{
/*!
\brief Saves the current configuration in the stream `output`.
\brief saves the current configuration in the stream `output`.
This allows to easily save and recover a specific classification
configuration.
@@ -302,7 +302,7 @@ public:
#endif
/*!
\brief Loads a configuration from the stream `input`.
\brief loads a configuration from the stream `input`.
The input file should be a GZIP container written by the
`save_configuration()` method. The feature set of the classifier
Classification/include/CGAL/Classification/ETHZ/internal/dataview.h
+12 -12
View File
@@ -79,17 +79,17 @@ struct DataView2D {
{
return *(data + row_step * row_idx + col_step * col_idx);
}
//! \brief Return a 1D view of a row
//! \brief returns a 1D view of a row
DataView1D<ElementType> row(size_t row_idx)
{
return DataView1D<ElementType>(data + row_step * row_idx, cols, col_step);
}
//! \brief Return a 1D view of a column
//! \brief returns a 1D view of a column
DataView1D<ElementType> col(size_t col_idx)
{
return DataView1D<ElementType>(data + col_step * col_idx, rows, row_step);
}
//! \brief Return a new view, using a subset of rows
//! \brief returns a new view, using a subset of rows
DataView2D row_range(size_t start_row, size_t end_row) const
{
DataView2D ret(*this);
@@ -97,7 +97,7 @@ struct DataView2D {
ret.rows = end_row - start_row;
return ret;
}
//! \brief Return a new view, using a subset of columns
//! \brief returns a new view, using a subset of columns
DataView2D col_range(size_t start_col, size_t end_col) const
{
DataView2D ret(*this);
@@ -105,7 +105,7 @@ struct DataView2D {
ret.cols = end_col - start_col;
return ret;
}
//! \brief Transpose the matrix (actually done by swapping the steps, no
//! \brief transposes the matrix (actually done by swapping the steps, no
// copying)
DataView2D transpose() const
{
@@ -124,23 +124,23 @@ struct DataView2D {
{
return DataView2D(vec.data, 1, vec.num_elements);
}
//! \brief Return the number of elements in this view
//! \brief returns the number of elements in this view
size_t num_elements() { return rows * cols; }
//! \brief Return true if the view is empty (no elements)
//! \brief returns true if the view is empty (no elements)
bool empty() { return num_elements() == 0; }
//! \brief Return true if rows in this view are continuous in memory
//! \brief returns true if rows in this view are continuous in memory
bool row_continuous() {
return col_step == 1;
}
//! \brief Return true if columns in this view are continuous in memory
//! \brief returns true if columns in this view are continuous in memory
bool col_continuous() {
return row_step == 1;
}
//! \brief Get pointer to row (only valid if row-continuous)
//! \brief gets pointer to row (only valid if row-continuous)
ElementType* row_pointer(size_t row_idx) {
return data + row_idx * row_step;
}
//! \brief Get pointer to column (only valid if column-continuous)
//! \brief gets pointer to column (only valid if column-continuous)
ElementType* col_pointer(size_t col_idx) {
return data + col_idx * col_step;
}
@@ -152,7 +152,7 @@ struct DataView2D {
size_t cols; //!< Number of columns in the view
};
//! \brief Determine if two 2D views have the same dimensions
//! \brief determines if two 2D views have the same dimensions
template <typename A, typename B>
bool equal_dims(DataView2D<A> view_a, DataView2D<B> view_b)
{
Classification/include/CGAL/Classification/Evaluation.h
+8 -8
View File
@@ -52,7 +52,7 @@ public:
/*!
\brief Instantiates an evaluation object and computes all
\brief instantiates an evaluation object and computes all
measurements.
\param labels labels used.
@@ -137,7 +137,7 @@ public:
/*!
\brief Returns the precision of the training for the given label.
\brief returns the precision of the training for the given label.
Precision is the number of true positives divided by the sum of
the true positives and the false positives.
@@ -150,7 +150,7 @@ public:
/*!
\brief Returns the recall of the training for the given label.
\brief returns the recall of the training for the given label.
Recall is the number of true positives divided by the sum of
the true positives and the false negatives.
@@ -163,7 +163,7 @@ public:
/*!
\brief Returns the \f$F_1\f$ score of the training for the given label.
\brief returns the \f$F_1\f$ score of the training for the given label.
\f$F_1\f$ score is the harmonic mean of `precision()` and `recall()`:
@@ -180,7 +180,7 @@ public:
}
/*!
\brief Returns the intersection over union of the training for the
\brief returns the intersection over union of the training for the
given label.
Intersection over union is the number of true positives divided by
@@ -199,7 +199,7 @@ public:
/*!
\brief Returns the accuracy of the training.
\brief returns the accuracy of the training.
Accuracy is the total number of true positives divided by the
total number of provided inliers.
@@ -207,13 +207,13 @@ public:
float accuracy() const { return m_accuracy; }
/*!
\brief Returns the mean \f$F_1\f$ score of the training over all
\brief returns the mean \f$F_1\f$ score of the training over all
labels (see `f1_score()`).
*/
float mean_f1_score() const { return m_mean_f1; }
/*!
\brief Returns the mean intersection over union of the training
\brief returns the mean intersection over union of the training
over all labels (see `intersection_over_union()`).
*/
float mean_intersection_over_union() const { return m_mean_iou; }
Classification/include/CGAL/Classification/Feature_base.h
+3 -3
View File
@@ -42,18 +42,18 @@ public:
/// \endcond
/*!
\brief Returns the name of the feature (initialized to
\brief returns the name of the feature (initialized to
`abstract_feature` for `Feature_base`).
*/
const std::string& name() const { return m_name; }
/*!
\brief Changes the name of the feature.
\brief changes the name of the feature.
*/
void set_name (const std::string& name) { m_name = name; }
/*!
\brief Returns the value taken by the feature for at the item for
\brief returns the value taken by the feature for at the item for
the item at position `index`. This method must be implemented by
inherited classes.
*/
Classification/include/CGAL/Classification/Feature_set.h
+9 -9
View File
@@ -33,7 +33,7 @@ namespace Classification {
/*!
\ingroup PkgClassificationFeature
\brief Set of features (see `Feature_base`) used as input by
\brief sets of features (see `Feature_base`) used as input by
classification algorithms. This class handles both the instantiation,
the addition and the deletion of features.
@@ -63,7 +63,7 @@ public:
/// @{
/*!
\brief Creates an empty feature set.
\brief creates an empty feature set.
*/
Feature_set()
#ifdef CGAL_LINKED_WITH_TBB
@@ -89,7 +89,7 @@ public:
/// @{
/*!
\brief Instantiates a new feature and adds it to the set.
\brief instantiates a new feature and adds it to the set.
If several calls of `add()` are surrounded by
`begin_parallel_additions()` and `end_parallel_additions()`, they
@@ -158,7 +158,7 @@ public:
/*!
\brief Removes a feature.
\brief removes a feature.
\param feature the handle to feature type that must be removed.
@@ -177,7 +177,7 @@ public:
}
/*!
\brief Removes all features.
\brief removes all features.
*/
void clear ()
{
@@ -193,7 +193,7 @@ public:
#if defined(CGAL_LINKED_WITH_TBB) || defined(DOXYGEN_RUNNING)
/*!
\brief Initializes structures to compute features in parallel.
\brief initializes structures to compute features in parallel.
If the user wants to add features in parallel, this function
should be called before making several calls of `add()`. After the
@@ -217,7 +217,7 @@ public:
/*!
\brief Waits for the end of parallel feature computation and
\brief waits for the end of parallel feature computation and
clears dedicated data structures afterwards.
If the user wants to add features in parallel, this function
@@ -247,7 +247,7 @@ public:
/// @{
/*!
\brief Returns how many features are defined.
\brief returns how many features are defined.
*/
std::size_t size() const
{
@@ -256,7 +256,7 @@ public:
/*!
\brief Returns the \f$i^{th}\f$ feature.
\brief returns the \f$i^{th}\f$ feature.
*/
Feature_handle operator[](std::size_t i) const
{
Classification/include/CGAL/Classification/Label_set.h
+7 -7
View File
@@ -25,7 +25,7 @@ namespace Classification {
/*!
\ingroup PkgClassificationLabel
\brief Set of `Label` used as input by classification
\brief sets of `Label` used as input by classification
algorithms.
*/
@@ -39,7 +39,7 @@ public:
Label_set() { }
/*!
\brief Initializes the set with the provided `labels` names.
\brief initializes the set with the provided `labels` names.
*/
Label_set (const std::initializer_list<const char*>& labels)
{
@@ -52,7 +52,7 @@ public:
/// \endcond
/*!
\brief Adds a label.
\brief adds a label.
\note Names are not used for identification: two labels in the
same set can have the same name (but not the same handle).
@@ -69,7 +69,7 @@ public:
}
/*!
\brief Removes a label.
\brief removes a label.
\param label the handle to the label that must be removed.
@@ -93,7 +93,7 @@ public:
}
/*!
\brief Returns how many labels are defined.
\brief returns how many labels are defined.
*/
std::size_t size () const
{
@@ -101,7 +101,7 @@ public:
}
/*!
\brief Returns the \f$i^{th}\f$ label.
\brief returns the \f$i^{th}\f$ label.
*/
Label_handle operator[] (std::size_t i) const
{
@@ -110,7 +110,7 @@ public:
/*!
\brief Removes all labels.
\brief removes all labels.
*/
void clear ()
{
Classification/include/CGAL/Classification/Local_eigen_analysis.h
+3 -3
View File
@@ -454,7 +454,7 @@ public:
/// @{
/*!
\brief Returns the estimated unoriented normal vector of the point at position `index`.
\brief returns the estimated unoriented normal vector of the point at position `index`.
\tparam GeomTraits model of \cgal Kernel.
*/
template <typename GeomTraits>
@@ -467,7 +467,7 @@ public:
}
/*!
\brief Returns the estimated local tangent plane of the point at position `index`.
\brief returns the estimated local tangent plane of the point at position `index`.
\tparam GeomTraits model of \cgal Kernel.
*/
template <typename GeomTraits>
@@ -481,7 +481,7 @@ public:
}
/*!
\brief Returns the normalized eigenvalues of the point at position `index`.
\brief returns the normalized eigenvalues of the point at position `index`.
*/
Eigenvalues eigenvalue (std::size_t index) const
{
Classification/include/CGAL/Classification/Mesh_feature_generator.h
+12 -12
View File
@@ -55,7 +55,7 @@ namespace Classification {
/*!
\ingroup PkgClassificationMesh
\brief Generates a set of generic features for surface mesh
\brief generates a set of generic features for surface mesh
classification.
This class takes care of computing and storing all necessary data
@@ -231,7 +231,7 @@ public:
/// @{
/*!
\brief Initializes a feature generator from an input range.
\brief initializes a feature generator from an input range.
If not provided by the user, The size of the smallest scale is
automatically estimated using a method equivalent to
@@ -301,7 +301,7 @@ public:
/*!
\brief Generate geometric features based on face information.
\brief generates geometric features based on face information.
At each scale, the following features are generated:
@@ -320,7 +320,7 @@ public:
}
/*!
\brief Generate geometric features based on point position information.
\brief generates geometric features based on point position information.
At each scale, the following features are generated by considering
the mesh as a point cloud through `PointMap`:
@@ -356,19 +356,19 @@ public:
/// @{
/*!
\brief Returns the bounding box of the input point set.
\brief returns the bounding box of the input point set.
*/
const Iso_cuboid_3& bbox() const { return m_bbox; }
/*!
\brief Returns the neighborhood structure at scale `scale`.
\brief returns the neighborhood structure at scale `scale`.
*/
const Neighborhood& neighborhood(std::size_t scale = 0) const { return (*m_scales[scale]->neighborhood); }
/*!
\brief Returns the planimetric grid structure at scale `scale`.
\brief returns the planimetric grid structure at scale `scale`.
*/
const Planimetric_grid& grid(std::size_t scale = 0) const { return *(m_scales[scale]->grid); }
/*!
\brief Returns the local eigen analysis structure at scale `scale`.
\brief returns the local eigen analysis structure at scale `scale`.
*/
const Local_eigen_analysis& eigen(std::size_t scale = 0) const { return *(m_scales[scale]->eigen); }
@@ -378,26 +378,26 @@ public:
/// @{
/*!
\brief Returns the number of scales that were computed.
\brief returns the number of scales that were computed.
*/
std::size_t number_of_scales() const { return m_scales.size(); }
/*!
\brief Returns the grid resolution at scale `scale`. This
\brief returns the grid resolution at scale `scale`. This
resolution is the length and width of a cell of the
`Planimetric_grid` defined at this scale.
*/
float grid_resolution(std::size_t scale = 0) const { return m_scales[scale]->grid_resolution(); }
/*!
\brief Returns the radius used for neighborhood queries at scale
\brief returns the radius used for neighborhood queries at scale
`scale`. This radius is the smallest radius that is relevant from
a geometric point of view at this scale (that is to say that
encloses a few cells of `Planimetric_grid`).
*/
float radius_neighbors(std::size_t scale = 0) const { return m_scales[scale]->radius_neighbors(); }
/*!
\brief Returns the radius used for digital terrain modeling at
\brief returns the radius used for digital terrain modeling at
scale `scale`. This radius represents the minimum size of a
building at this scale.
*/
Classification/include/CGAL/Classification/Mesh_neighborhood.h
+2 -2
View File
@@ -172,7 +172,7 @@ public:
/// @{
/*!
\brief Returns a 1-ring neighbor query object.
\brief returns a 1-ring neighbor query object.
*/
One_ring_neighbor_query one_ring_neighbor_query () const
{
@@ -180,7 +180,7 @@ public:
}
/*!
\brief Returns an N-ring neighbor query object.
\brief returns an N-ring neighbor query object.
*/
N_ring_neighbor_query n_ring_neighbor_query (const std::size_t n) const
{
Classification/include/CGAL/Classification/OpenCV/Random_forest_classifier.h
+4 -4
View File
@@ -71,7 +71,7 @@ public:
/// @{
/*!
\brief Instantiates the classifier using the sets of `labels` and `features`.
\brief instantiates the classifier using the sets of `labels` and `features`.
Parameters documentation is copy-pasted from [the official documentation of OpenCV](https://docs.opencv.org/2.4/modules/ml/doc/random_trees.html). For more details on this method, please refer to it.
@@ -129,7 +129,7 @@ public:
/// @{
/*!
\brief Runs the training algorithm.
\brief runs the training algorithm.
From the set of provided ground truth, this algorithm estimates
sets up the random trees that produce the most accurate result
@@ -262,7 +262,7 @@ public:
/*!
\brief Saves the current configuration in the file named `filename`.
\brief saves the current configuration in the file named `filename`.
This allows to easily save and recover a specific classification
configuration.
@@ -276,7 +276,7 @@ public:
}
/*!
\brief Loads a configuration from the file named `filename`.
\brief loads a configuration from the file named `filename`.
The input file should be in the XML format written by the
`save_configuration()` method. The feature set of the classifier
Classification/include/CGAL/Classification/Planimetric_grid.h
+8 -8
View File
@@ -266,7 +266,7 @@ public:
/*!
\brief Returns the resolution of the grid.
\brief returns the resolution of the grid.
*/
float resolution() const
{
@@ -274,14 +274,14 @@ public:
}
/*!
\brief Returns the number of cells along the X-axis.
\brief returns the number of cells along the X-axis.
*/
std::size_t width() const
{
return m_width;
}
/*!
\brief Returns the number of cells along the Y-axis.
\brief returns the number of cells along the Y-axis.
*/
std::size_t height() const
{
@@ -300,7 +300,7 @@ public:
/// \endcond
/*!
\brief Returns the begin iterator on the indices of the points
\brief returns the begin iterator on the indices of the points
lying in the cell at position `(x,y)`.
*/
iterator indices_begin(std::size_t x, std::size_t y) const
@@ -311,7 +311,7 @@ public:
}
/*!
\brief Returns the past-the-end iterator on the indices of the points
\brief returns the past-the-end iterator on the indices of the points
lying in the cell at position `(x,y)`.
*/
iterator indices_end(std::size_t x, std::size_t y) const
@@ -322,7 +322,7 @@ public:
}
/*!
\brief Returns `false` if the cell at position `(x,y)` is empty, `true` otherwise.
\brief returns `false` if the cell at position `(x,y)` is empty, `true` otherwise.
*/
bool has_points(std::size_t x, std::size_t y) const
{
@@ -336,7 +336,7 @@ public:
}
/*!
\brief Returns the `x` grid coordinate of the point at position `index`.
\brief returns the `x` grid coordinate of the point at position `index`.
*/
std::size_t x(std::size_t index) const
{
@@ -350,7 +350,7 @@ public:
return m_lower_scale->x(index) / 2;
}
/*!
\brief Returns the `y` grid coordinate of the point at position `index`.
\brief returns the `y` grid coordinate of the point at position `index`.
*/
std::size_t y(std::size_t index) const
{
Classification/include/CGAL/Classification/Point_set_feature_generator.h
+14 -14
View File
@@ -57,7 +57,7 @@ namespace Classification {
/*!
\ingroup PkgClassificationPointSet
\brief Generates a set of generic features for point set
\brief generates a set of generic features for point set
classification.
This class takes care of computing and storing all necessary data
@@ -233,7 +233,7 @@ public:
/// @{
/*!
\brief Initializes a feature generator from an input range.
\brief initializes a feature generator from an input range.
If not provided by the user, The size of the smallest scale is
automatically estimated using a method equivalent to
@@ -300,7 +300,7 @@ public:
/*!
\brief Generate geometric features based on point position information.
\brief generates geometric features based on point position information.
At each scale, the following features are generated:
@@ -337,7 +337,7 @@ public:
}
/*!
\brief Generate geometric features based on normal vector information.
\brief generates geometric features based on normal vector information.
Generates the version of `CGAL::Classification::Feature::Verticality` based on normal vectors.
@@ -356,7 +356,7 @@ public:
}
/*!
\brief Generate geometric features based on point color information.
\brief generates geometric features based on point color information.
Generates `CGAL::Classification::Feature::Color_channel` with
channels `HUE`, `SATURATION` and `VALUE`.
@@ -377,7 +377,7 @@ public:
}
/*!
\brief Generate geometric features based on echo information.
\brief generates geometric features based on echo information.
At each scale, generates `CGAL::Classification::Feature::Echo_scatter`.
@@ -402,19 +402,19 @@ public:
/// @{
/*!
\brief Returns the bounding box of the input point set.
\brief returns the bounding box of the input point set.
*/
const Iso_cuboid_3& bbox() const { return m_bbox; }
/*!
\brief Returns the neighborhood structure at scale `scale`.
\brief returns the neighborhood structure at scale `scale`.
*/
const Neighborhood& neighborhood(std::size_t scale = 0) const { return (*m_scales[scale]->neighborhood); }
/*!
\brief Returns the planimetric grid structure at scale `scale`.
\brief returns the planimetric grid structure at scale `scale`.
*/
const Planimetric_grid& grid(std::size_t scale = 0) const { return *(m_scales[scale]->grid); }
/*!
\brief Returns the local eigen analysis structure at scale `scale`.
\brief returns the local eigen analysis structure at scale `scale`.
*/
const Local_eigen_analysis& eigen(std::size_t scale = 0) const { return *(m_scales[scale]->eigen); }
@@ -424,26 +424,26 @@ public:
/// @{
/*!
\brief Returns the number of scales that were computed.
\brief returns the number of scales that were computed.
*/
std::size_t number_of_scales() const { return m_scales.size(); }
/*!
\brief Returns the grid resolution at scale `scale`. This
\brief returns the grid resolution at scale `scale`. This
resolution is the length and width of a cell of the
`Planimetric_grid` defined at this scale.
*/
float grid_resolution(std::size_t scale = 0) const { return m_scales[scale]->grid_resolution(); }
/*!
\brief Returns the radius used for neighborhood queries at scale
\brief returns the radius used for neighborhood queries at scale
`scale`. This radius is the smallest radius that is relevant from
a geometric point of view at this scale (that is to say that
encloses a few cells of `Planimetric_grid`).
*/
float radius_neighbors(std::size_t scale = 0) const { return m_scales[scale]->radius_neighbors(); }
/*!
\brief Returns the radius used for digital terrain modeling at
\brief returns the radius used for digital terrain modeling at
scale `scale`. This radius represents the minimum size of a
building at this scale.
*/
Classification/include/CGAL/Classification/Point_set_neighborhood.h
+2 -2
View File
@@ -276,7 +276,7 @@ public:
/// @{
/*!
\brief Returns a neighbor query object with fixed number of neighbors `k`.
\brief returns a neighbor query object with fixed number of neighbors `k`.
*/
K_neighbor_query k_neighbor_query (const unsigned int k) const
{
@@ -284,7 +284,7 @@ public:
}
/*!
\brief Returns a neighbor query object with fixed radius `radius`.
\brief returns a neighbor query object with fixed radius `radius`.
*/
Sphere_neighbor_query sphere_neighbor_query (const float radius) const
{
Classification/include/CGAL/Classification/Sum_of_weighted_features_classifier.h
+8 -8
View File
@@ -163,7 +163,7 @@ public:
/*!
\brief Instantiates the classifier using the sets of `labels` and `features`.
\brief instantiates the classifier using the sets of `labels` and `features`.
\note If the label set of the feature set are modified after
instantiating this object (addition of removal of a label and/or of
@@ -190,7 +190,7 @@ public:
/// @{
/*!
\brief Sets the weight of `feature` (`weight` must be positive).
\brief sets the weight of `feature` (`weight` must be positive).
*/
void set_weight (Feature_handle feature, float weight)
{
@@ -204,7 +204,7 @@ public:
/// \endcond
/*!
\brief Returns the weight of `feature`.
\brief returns the weight of `feature`.
*/
float weight (Feature_handle feature) const
{
@@ -218,7 +218,7 @@ public:
/// \endcond
/*!
\brief Sets the `effect` of `feature` on `label`.
\brief sets the `effect` of `feature` on `label`.
*/
void set_effect (Label_handle label, Feature_handle feature,
Effect effect)
@@ -234,7 +234,7 @@ public:
/// \endcond
/*!
\brief Returns the `effect` of `feature` on `label`.
\brief returns the `effect` of `feature` on `label`.
*/
Effect effect (Label_handle label, Feature_handle feature) const
{
@@ -269,7 +269,7 @@ public:
/// @{
/*!
\brief Runs the training algorithm.
\brief runs the training algorithm.
From the set of provided ground truth, this algorithm estimates
the sets of weights and effects that produce the most accurate
@@ -636,7 +636,7 @@ public:
/// @{
/*!
\brief Saves the current configuration in the stream `output`.
\brief saves the current configuration in the stream `output`.
This allows to easily save and recover a specific classification
configuration, that is to say:
@@ -694,7 +694,7 @@ public:
}
/*!
\brief Loads a configuration from the stream `input`. A
\brief loads a configuration from the stream `input`. A
configuration is a set of weights and effects.
The input file should be in the XML format written by the
Classification/include/CGAL/Classification/TensorFlow/Neural_network_classifier.h
+4 -4
View File
@@ -113,7 +113,7 @@ public:
/// @{
/*!
\brief Instantiates the classifier using the sets of `labels` and `features`.
\brief instantiates the classifier using the sets of `labels` and `features`.
*/
Neural_network_classifier (const Label_set& labels,
@@ -204,7 +204,7 @@ public:
/// @{
/*!
\brief Runs the training algorithm.
\brief runs the training algorithm.
From the set of provided ground truth, this algorithm constructs a
neural network and applies an Adam optimizer to set up the weights
@@ -446,7 +446,7 @@ public:
/// @{
/*!
\brief Saves the current configuration in the stream `output`.
\brief saves the current configuration in the stream `output`.
This allows to easily save and recover a specific classification
configuration, that is to say:
@@ -527,7 +527,7 @@ public:
}
/*!
\brief Loads a configuration from the stream `input`.
\brief loads a configuration from the stream `input`.
The input file should be in the XML format written by the
`save_configuration()` method. The feature set of the classifier
Classification/include/CGAL/Classification/classify.h
+3 -3
View File
@@ -320,7 +320,7 @@ namespace internal {
/*!
\ingroup PkgClassificationMain
\brief Runs the classification algorithm without any regularization.
\brief runs the classification algorithm without any regularization.
There is no relationship between items, the classification energy
is only minimized itemwise. This method is quick but produces
@@ -410,7 +410,7 @@ namespace internal {
/*!
\ingroup PkgClassificationMain
\brief Runs the classification algorithm with a local smoothing.
\brief runs the classification algorithm with a local smoothing.
The computed classification energy is smoothed on a user defined
local neighborhood of items. This method is a compromise between
@@ -480,7 +480,7 @@ namespace internal {
/*!
\ingroup PkgClassificationMain
\brief Runs the classification algorithm with a global
\brief runs the classification algorithm with a global
regularization based on a graph cut.
The computed classification energy is globally regularized through