Description
Usage
Arguments
Details
Value
Examples
View source: R/kml3d.r
parKml3d
is a constructor of object ParKml
that provide adequate default value for the use of function kml3d
.
 (saveFreq = 100, maxIt = 200, imputationMethod = "copyMean",
distanceName = "euclidean3d", = 2, distance = () {
}, centerMethod = meanNA, startingCond = "nearlyAll", nbCriterion =100,=)

saveFreq 
[numeric] : Long computations can take several
days. So it is possible to save the object ClusterLongData3d
on which works kml3d once in a while. saveFreq
defines the frequency of the saving
process. The ClusterLongData3d is saved every saveFreq
clustering calculations. The object is saved in the file
objectName.Rdata in the curent folder.

maxIt 
[numeric] : Set a limit to the number of iteration if
convergence is not reached.

imputationMethod 
[character] : the calculation of quality
criterion can not be done if some value are
missing. imputationMethod define the method use to impute the
missing value. See imputation for detail.

distanceName 
[character] : name of the
distance used by kmeans. If the distanceName is "euclidean3d", a compiled optimized version specificaly design for
jointtrajectories version is used. Otherwise, the function define in
the slot distance is used.

power 
[numeric] : If distanceName="minkowski" , this define
the power that will be used.

distance 
[numeric < function(trajA,trajB)] : function that computes the
distance between two trajectories. If no function is specified, the Euclidian
distance with Gower adjustment (to deal with missing value) is
used.

centerMethod 
[numeric <
function(vector(numeric))] : kmeans algorithm computes the centers of
each cluster. It is possible to personalize the definition of
"center" by defining a function "centerMethod". This function should
take a vector of numeric as argument and return a single numeric the
center of the vector.

startingCond 
[character] : specifies the starting
condition. Should be one of "randomAll", "randomK", "maxDist",
"kmeans++", "kmeans+", "kmeans" or "kmeans–" (see
initializePartition for details). It
also could take two specifics values: "all" stands for
c("maxDist","kmeans") then an alternance of "kmeans–" and
"randomK" while "nearlyAll" stands for
"kmeans" then an alternance of "kmeans–" and "randomK".

nbCriterion 
[numeric] : set the maximum number of
quality criterion that are display on the graph (since displaying
a high criterion number an slow down the overall process, the
default value is 100).

scale 
[logical] : if TRUE, then the data will be
automaticaly scaled (using the function scale with
default values) before the execution of kmeans on joint
trajectories. Then the data
will be restore (using the function restoreRealData )
just before the end of the function kml3d . This option
has no effect on kml .

parKml3d
is a constructor of object ParKml
that provide adequate default value for the use of function kml3d
.
An object ParKml
.
 ### Generation of some data
cld1 < ((15,15,15))
### Setting two different set of option :
(option1 < ())
(option2 < (centerMethod=(x)(x,na.rm=)))
### Running kml. Formaly, the second exemple is 'kmedian'
(cld1,4,1,toPlot="both",parAlgo=option1)
(cld1,4,1,toPlot="both",parAlgo=option2)

kml3d documentation built on Aug. 8, 2017, 9:09 a.m.