CORElearn-internal {CORElearn} | R Documentation |
Internal structures of CORElearn C++ part
Description
The package CORElearn is an R port of CORElearn data mining system. This document is a short description of the C++ part which can also serve as a standalone Linux or Windows data mining system, its organization and main classes and data structures.
Details
The C++ part is called from R functions collected in file Rinterface.R
.
The C++ functions called from R and providing interface to R are collected in Rfront.cpp
and Rconvert.cpp
. The front end for standalone version is in file frontend.cpp
.
For many parts of the code there are two variants, classification and regression one.
Regression part usually has Reg
somewhere in its name.
The main classes are
-
marray, mmatrix
are templates for storing vectors and matrixes -
dataStore
contains data storage and data manipulation methods, of which the most important are-
mmatrix<int> DiscData, DiscPredictData
contain values of discrete attributes and class for training and prediction (optional). In classification column 0 always stores class values. -
mmatrix<double> ContData, ContPredictData
contain values of numeric attribute and prediction values for training and prediction (optional). In regression column 0 always stores target values. -
marray<attribute> AttrDesc
with information about attributes' types, number of values, min, max, column index in DiscData or ContData, ...
-
-
estimation, estimationReg
evaluate attributes with different purposes: decision/regression tree splitting, binarization, discretization, constructive induction, feature selection, etc. Because of efficiency these classes store its own data in-
mmatrix<int> DiscValues
containing discrete attributes and class values, -
mmatrix<double> ContValues
containing numeric attribute and prediction values.
-
-
Options
stores and handles all the parameters of the system. -
featureTree, regressionTree
build all the models, predict with them, and create output.
Author(s)
Marko Robnik-Sikonja
See Also
CORElearn
, CoreModel
, predict.CoreModel
,
modelEval
, attrEval
, ordEval
,
plot.ordEval
, helpCore
, paramCoreIO
,
infoCore
, versionCore
.