BOW

The documentation of the bow module.

The pyts.bop module includes bag-of-patterns algorithms.

class pyts.bow.BOW(window_size=4, numerosity_reduction=True)

Bag Of Words.

Parameters:

window_size : int (default = 4)

Size of the window (i.e. the size of each word).

numerosity_reduction : bool (default = True)

If True, delete all but one occurence of back to back identical occurences of the same words.

Methods

fit([X, y])	Pass.
fit_transform(X[, y])	Fit to data, then transform it.
get_params([deep])	Get parameters for this estimator.
set_params(**params)	Set the parameters of this estimator.
transform(X)	Transform a sequence of letters into a sequence of words.

fit(X=None, y=None)

Pass.

Parameters:

X

ignored

y

Ignored

transform(X)

Transform a sequence of letters into a sequence of words.

Parameters:

X : array-like, shape = [n_samples, n_features]

Returns:

X_new : array-like, size = [n_samples]

Transformed data.