SAX¶
-
class
sktime.transformations.panel.dictionary_based.
SAX
(word_length=8, alphabet_size=4, window_size=12, remove_repeat_words=False, save_words=False, return_pandas_data_series=True)[source]¶ SAX (Symbolic Aggregate approXimation) Transformer, as described in Jessica Lin, Eamonn Keogh, Li Wei and Stefano Lonardi, “Experiencing SAX: a novel symbolic representation of time series” Data Mining and Knowledge Discovery, 15(2):107-144 Overview: for each series:
run a sliding window across the series for each window
shorten the series with PAA (Piecewise Approximate Aggregation) discretise the shortened series into fixed bins form a word from these discrete values
by default SAX produces a single word per series (window_size=0). SAX returns a pandas data frame where column 0 is the histogram (sparse pd.series) of each series.
- Parameters
word_length (int, length of word to shorten window to (using) –
(default 8) (PAA)) –
alphabet_size (int, number of values to discretise each value) –
(default to 4) (to) –
window_size (int, size of window for sliding. Input series) –
for whole series transform (default to 12) (length) –
remove_repeat_words (boolean, whether to use numerosity reduction () –
False) (default) –
save_words (boolean, whether to use numerosity reduction () –
False) –
return_pandas_data_series (boolean, default = True) – set to true to return Pandas Series as a result of transform. setting to true reduces speed significantly but is required for automatic test.