clda (version 0.1)

clda.classify: cLDA classify

Description

Classify the time series and obtain the distances between the time series and the centroids of each class.

Usage

clda.classify(model, Data)

Arguments

model

An object returned by the function clda.model.

Data

Matrix of time series on the rows.

Value

A list containing the predicted labels of the time series and a matrix of distances between the time series and the centroids after applying the filters obtained by clda.model.

See Also

clda.model

Examples

# NOT RUN {
## Generating 200 time series of length 100 with label 1
time_series_signal_1 = sin(matrix(runif(200*100),nrow = 200,ncol = 100))
time_series_error_1 = matrix(rnorm(200*100),nrow = 200,ncol = 100)
time_series_w_label_1 = time_series_signal_1 + time_series_error_1
## Generating another 200 time series of length 100 with label 2
time_series_signal_2 = cos(matrix(runif(200*100),nrow = 200,ncol = 100))
time_series_error_2 = matrix(rnorm(200*100),nrow = 200,ncol = 100)
time_series_w_label_2 = time_series_signal_2 + time_series_error_2
## Join the time series data in one matrix
time_series_data = rbind(time_series_w_label_1,time_series_w_label_2)
label_time_series   = c(rep(1,200),rep(2,200))
clda_model <- clda.model(time_series_data,label_time_series)
## Create a test set
## data with label 1
Data_test_label_1 = sin(matrix(runif(50*100),nrow = 50,ncol = 100))
## data with label 2
Data_test_label_2 = cos(matrix(runif(50*100),nrow = 50,ncol = 100))
## join data into a single matrix
Data_test = rbind(Data_test_label_1,Data_test_label_2)
## obtain the labels and distances of each time series
clda.classify(clda_model,Data_test)
# }