Comments (2)
I'm looking for the equivalence of this R-implementation in Java.
`# classify the test data
labels_predicted = rep(-1, length(CBF[["labels_test"]]))
labels_test = CBF[["labels_test"]]
data_test = CBF[["data_test"]]
for (i in c(1:length(data_test[,1])))
{
print(paste(i))
series = data_test[i,]
bag = series_to_wordbag(series, w, p, a, "exact", 0.01)
cosines = cosine_sim(list("bag"=bag, "tfidf" = tfidf))
if (!any(is.na(cosines$cosines))) {
labels_predicted[i] = which(cosines$cosines == max(cosines$cosines))
}
}
`
Taken from your SAX-VSM R-page https://github.com/jMotif/jmotif-R
from sax.
This functionality is not a part of this library and will not be. SAX lib is concerned with the discretization transform and the hot-sax algorithm. Sax-vsm lib implements the thing you want.
from sax.
Related Issues (16)
- Maven repo availability HOT 1
- PAA doesn't behave as expected for series whose length is not multiple of paa size HOT 2
- SAXProcessor doesn't process series of length = window size
- Approx distance computation needs to be fixed.
- Approx distance should account for the alphabet.
- do you have any examples of using shingles in time series classification? HOT 1
- Generalization of Alphabet implementation HOT 3
- Performance improvement in TSProcessor
- TSProcessor and SAXProcessor exception handling improvement
- Feature Request: String to PAA
- Using sax on gps points
- any python version?
- Tests shouldn't print much output.
- Rule thrown away makes it back after the check loop.
- HOTSAX fails if each subsequence of time series has a NN with a distance 0 HOT 1
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from sax.