classifyGENEA {GENEAclassify}

Classify Data into Categories defined in an rpart GENEA fit

Description

Perform classification on segmented GENEActiv bin data using an rpart GENEA training fit.

Usage

classifyGENEA(
  testfile,
  start = NULL,
  end = NULL,
  Use.Timestamps = FALSE,
  radians = FALSE,
  mmap.load = (.Machine$sizeof.pointer >= 8),
  trainingfit = trainingFit,
  newdata,
  allprobs = FALSE,
  setinf = 100,
  outputname = "_classified",
  outputdir = "GENEAclassification",
  datacols = "default",
  changepoint = c("UpDownDegrees", "TempFreq", "UpDownFreq", "UpDownMean", "UpDownVar",
    "UpDownMeanVar", "DegreesMean", "DegreesVar", "DegreesMeanVar",
    "UpDownMeanVarDegreesMeanVar", "UpDownMeanVarMagMeanVar"),
  penalty = "Manual",
  pen.value1 = 40,
  pen.value2 = 400,
  intervalseconds = 30,
  mininterval = 5,
  samplefreq = 100,
  filterorder = 2,
  boundaries = c(0.5, 5),
  Rp = 3,
  plot.it = FALSE,
  hysteresis = 0.1,
  stft_win = 10,
  plot.seg = FALSE,
  plot.seg.outputfile = "Changepoint",
  verbose = TRUE,
  ...
)

Arguments

testfile

character string stating path to a GENEActiv bin file, or a folder containing GENEActiv bin files.

start

Where to start reading observations.

end

Where to end reading observations.

Use.Timestamps

To use timestamps as the start and end time values this has to be set to TRUE. (Default FALSE)

radians

calculate degrees rotation in radians.

mmap.load

Default is (.Machine$sizeof.pointer >= 8). see mmap for more details

trainingfit

a GENEA rpart object created by createGENEAmodel that gives the decision tree that was fitted from the training data. These are the parameters used to predict the new data.

newdata

a new data frame that is to be classified (provide instead of testfile). The data must contain the features named in the trainingfit.

allprobs

single logical should all estimated probabilities be reported rather than probability of selected class (default FALSE).

setinf

single numeric an arbitrary value to replace Inf in calculated columns or NA to ignore Inf values. (default 100). -setinf is used to replace -Inf. Alternatively, use setinf NULL to leave Inf as is.

outputname

file name root (excluding extension) for saving the classification output (default "classified").

outputdir

absolute or relative path to directory in which artifacts (plot and changes files) should be created or NULL (default "GENEAclassification").

datacols

a vector constructed 'column.summary' or 'default'. See segmentation for details.

changepoint

defines the change point analysis to use. UpDownDegrees performs the change point analysis on the variance of arm elevation and wrist rotation. TempFreq performs a change point on the variance in the temeprature and Frequency (Typically better for sleep behaviours)

penalty

single characgter, the penalty to use for changepoint detection. default ("SIC")

pen.value1

Value of the type 1 error required when penalty is "Asymptotic".

pen.value2

Default set as NULL and so equals pen.value1 if no input.

intervalseconds

An integer number of seconds between 5 and 30 during which at most one changepoint may occur.

mininterval

single numeric that defines the smallest changepoint initially found. Passed to cpt.var as the variable minseglen

samplefreq

The sampling frequency of the data, in hertz, when calculating the step number. (default 100)

filterorder

The order of the filter applied with respect to the cheby options.

boundaries

to passed to the filter in the step counting algorithm.

Rp

the decibel level that the cheby filter takes. see cheby1

plot.it

(logical) Creates a plot showing the zero crossings counted by the step counting algorithm#' @param Centre Centres the xz signal about 0 when set to True.

hysteresis

The hysteresis applied after zero crossing. (default 100mg)

stft_win

numeric for the window to calculate the frequency of an event using the stft function.

plot.seg

(logical) Creates a plot displaying the changepoint locations

plot.seg.outputfile

The name of the png file created that shows the change points on a positionals plots.

verbose

single logical should additional progress reporting be printed at the console (default TRUE).

...

other arguments to be passed to dataImport, segmentation and other functions

Details

This function will apply the rules determined by the rpart GENEA decision tree passed to argument trainingfit to the columns of newdata to classify into classes (view using "levels").

Value

The function will return the data frame that was provided as newdata with additional columns.

1. Class, a factor indicating that the predicted category of the segment

2. p.Class, estimated probability that the prediction is correct

Alternatively, by setting argument allprobs to TRUE, a column constructed 'p.level' containing the estimated probability of each possible class will be returned instead.

Examples

## segData <- read.csv(system.file(package = "GENEAclassify", 
##       "testdata", "trainingData9.csv"))
## The training fit can be created by provided the file path to the training data
## in the function getTrainingData - see the help file for more details
## Uses the fitted decision tree to predict the segmented data
## class9 <- classifyGENEA(testfile = "trainingData9.csv",
##                         newdata = segData, 
##                         trainingfit = trainingFit)
## head(class9)
## table(class9$Class)