ProbKMA {funMoDisco} | R Documentation |
ProbKMA Class
Description
The 'ProbKMA' class is an R wrapper for the C++ implementation of the Probabilistic K-means Algorithm (ProbKMA) with local alignment. This class facilitates local clustering of functional data and functional motif discovery, as proposed in the paper 'Probabilistic K-means with local alignment for clustering and motif discovery in functional data', authored by Marzia A. Cremona and Francesca Chiaromonte.
Value
A 'ProbKMA' object from the C++ ProbKMA class.
Constructor
Create a 'ProbKMA' object using the following constructor:
prok <- new(ProbKMA, data$Y, data$V, params, data$P0, data$S0, "H1")
Parameters
- Y
A list containing functional data and possibly derivatives.
- params
An instance of the Parameters class, containing algorithm settings.
- P0
A matrix representing the initial membership probabilities.
- S0
A matrix representing the initial shift warping parameters.
- diss
A character string specifying the dissimilarity measure. Possible choices are:
''d0_L2''
''d1_L2''
''d0_d1_L2''
Usage
You can access and modify the 'ProbKMA' object with the following methods:
- Getters:
-
- prok$get_parameters()
Returns a list of parameters.
- prok$get_motifs()
Returns a list containing the motifs found.
- Setters:
-
- prok$set_P0(P)
Sets the membership matrix.
- prok$set_S0(S)
Sets the shift warping matrix.
- prok$set_parameters(param)
Sets parameters field by passing a list of parameters.
- Initialize Motifs:
-
- prok$reinit_motifs(c, d)
Reinitializes (empty) K motifs with dimension c_k x d.
- Run ProbKMA algorithm:
-
- prok$probKMA_run()
Runs the algorithm.
Author(s)
Niccolò Feresini and Riccardo Lazzarini