Data Mining Algorithms In R/Packages/CCMtools/learn.and.project.clusters

Description
This function (1) learns how to attribute days to clusters based on the sequence of predictors and associated sequence of clusters.

Usage
learn.and.project.clusters(DataCalibration, DataToBeProjected, cl.calibration, allocmet, Datas.Calibration)

Arguments

 * DataCalibration     Values of the predictor variable for the calibration set (can be a matrix).


 * DataToBeProjected    Values of the predictor variable for the projection set.


 * cl.calibration    Numerical vector corresponding to the sequence of clusters (i.e., calibration set).


 * allocmet   Name of the attribution method.(The 12 possibilities are: "Euclid.dist.A", "Euclid. dist.w1", "Euclid.dist.w2", "CART.A", "CART.w", "CART.A.and.w", "knnA", "knnA10", "Gaussian.A", "Gaussian.w", "MM", "MMw")


 * DataS.Calibration    Values of other predictor variables for the calibration set. This is sometimes  needed, according to the attribution method (allocmet) to be used (needed for  "Euclid.dist.w1", "Euclid.dist.w2", "CART.w", "CART.A.and.w", "Gaussian.w", "MMw").

Value
Returns a list with two objects:
 * cl  The sequence of clusters defined from the predictors for the projection set.
 * tot  Number of elements per cluster for projection set.

Author
M. Vrac (mathieu.vrac@lsce.ipsl.fr))