Node.c File Reference

#include "party.h"
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Functions

void C_prediction (const double *y, int n, int q, const double *weights, const double sweights, double *ans)
void C_Node (SEXP node, SEXP learnsample, SEXP weights, SEXP fitmem, SEXP controls, int TERMINAL, int depth)
SEXP R_Node (SEXP learnsample, SEXP weights, SEXP fitmem, SEXP controls)

Detailed Description

Node computations

Author:
Author
hothorn
Date:
Date
2009-06-16 09:17:31 +0200 (Tue, 16 Jun 2009)

Definition in file Node.c.


Function Documentation

void C_Node ( SEXP  node,
SEXP  learnsample,
SEXP  weights,
SEXP  fitmem,
SEXP  controls,
int  TERMINAL,
int  depth 
)

The main function for all node computations

Parameters:
node an initialized node (an S3 object!)
learnsample an object of class `LearningSample'
weights case weights
fitmem an object of class `TreeFitMemory'
controls an object of class `TreeControl'
TERMINAL logical indicating if this node will be a terminal node
depth an integer giving the depth of the current node

Definition at line 49 of file Node.c.

References C_GlobalTest(), C_init_nominalsplit(), C_init_orderedsplit(), C_max(), C_prediction(), C_split(), C_splitcategorical(), C_standardize(), C_tempweights(), C_whichmax(), get_dimension(), get_gtctrl(), get_levels(), get_mincriterion(), get_minsplit(), get_ninputs(), get_nobs(), get_ordering(), get_predict_trafo(), get_savesplitstats(), get_splitctrl(), get_splitstatistics(), get_test_trafo(), get_tgctrl(), get_tol(), get_transformation(), get_varctrl(), get_variable(), get_varmemory(), has_missings(), is_nominal(), ncol(), PL2_covarianceSym, PL2_expcovinfSym, PL2_expectationSym, PL2_inputsSym, PL2_linearstatisticSym, PL2_linexpcov2sampleSym, PL2_responsesSym, PL2_sumweightsSym, S3_SUMWEIGHTS, S3get_criterion(), S3get_maxcriterion(), S3get_prediction(), S3get_primarysplit(), S3get_splitpoint(), S3get_splitstatistics(), S3get_table(), S3get_teststat(), S3set_nodeterminal(), and S3set_variableID().

Referenced by C_TreeGrow(), and R_Node().

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void C_prediction ( const double *  y,
int  n,
int  q,
const double *  weights,
const double  sweights,
double *  ans 
)

Compute prediction of a node

Parameters:
y the response variable (raw numeric values or dummy encoded factor)
n number of observations
q number of columns of y
weights case weights
sweights sum of case weights
ans return value; the q-dimensional predictions

Definition at line 22 of file Node.c.

Referenced by C_Node().

SEXP R_Node ( SEXP  learnsample,
SEXP  weights,
SEXP  fitmem,
SEXP  controls 
)

R-interface to C_Node

Parameters:
learnsample an object of class `LearningSample'
weights case weights
fitmem an object of class `TreeFitMemory'
controls an object of class `TreeControl'

Definition at line 228 of file Node.c.

References C_init_node(), C_Node(), get_maxsurrogate(), get_ninputs(), get_nobs(), get_predict_trafo(), get_splitctrl(), ncol(), NODE_LENGTH, and PL2_responsesSym.

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