h2o.isax | R Documentation |
Compute the iSAX index for a DataFrame which is assumed to be numeric time series data
h2o.isax(x, num_words, max_cardinality, optimize_card = FALSE)
x |
an H2OFrame |
num_words |
Number of iSAX words for the timeseries. ie granularity along the time series |
max_cardinality |
Maximum cardinality of the iSAX word. Each word can have less than the max |
optimize_card |
An optimization flag that will find the max cardinality regardless of what is passed in for max_cardinality. |
An H2OFrame with the name of time series, string representation of iSAX word, followed by binary representation
https://www.cs.ucr.edu/~eamonn/iSAX_2.0.pdf
https://www.cs.ucr.edu/~eamonn/SAX.pdf
## Not run:
library(h2o)
h2o.init()
df <- h2o.createFrame(rows = 1, cols = 256, randomize = TRUE, value = 0,
real_range = 100, categorical_fraction = 0, factors = 0,
integer_fraction = 0, integer_range = 100, binary_fraction = 0,
binary_ones_fraction = 0, time_fraction = 0, string_fraction = 0,
missing_fraction = 0, has_response = FALSE, seed = 123)
df2 <- h2o.cumsum(df, axis = 1)
h2o.isax(df2, num_words = 10, max_cardinality = 10)
## End(Not run)
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