View source: R/ddalphaf.test.r
ddalphaf.getErrorRatePart | R Documentation |
Performs a benchmark procedure by partitioning the given data.
On each of times
steps size
observations are removed from the data, the functional DD-classifier is trained on these data and tested on the removed observations.
ddalphaf.getErrorRatePart(dataf, labels, size = 0.3, times = 10,
disc.type = c("LS", "comp"), ...)
dataf |
list containing lists (functions) of two vectors of equal length, named "args" and "vals": arguments sorted in ascending order and corresponding them values respectively |
labels |
list of output labels of the functional observations |
size |
the excluded sequences size. Either an integer between |
times |
the number of times the classifier is trained. |
disc.type |
type of the used discretization scheme. "LS" for |
... |
additional parameters passed to |
errors |
the part of incorrectly classified data (mean) |
errors_sd |
the standard deviation of errors |
errors_vec |
vector of errors |
time |
the mean training time |
time_sd |
the standard deviation of training time |
ddalphaf.train
to train the functional DD\alpha
-classifier,
ddalphaf.classify
for classification using functional DD\alpha
-classifier,
ddalphaf.test
to test the functional DD-classifier on particular learning and testing data,
ddalphaf.getErrorRateCV
to get error rate of the functional DD-classifier on particular data.
# load the fdata
df = dataf.growth()
stat <- ddalphaf.getErrorRatePart(dataf = df$dataf, labels = df$labels,
size = 0.3, times = 5,
adc.args = list(instance = "avr",
numFcn = 2,
numDer = 2))
cat("Classification error rate: ", stat$errors, ".\n", sep = "")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.