skmultiflow.transform.
WindowedMinmaxScaler
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero and one. For the training set we consider a window of a given length.
Defines the window size to compute min and max values.
Methods
get_info(self)
get_info
Collects and returns the information about the configuration of the estimator
get_params(self[, deep])
get_params
Get parameters for this estimator.
partial_fit(self, X[, y])
partial_fit
Partial fits the model.
partial_fit_transform(self, X[, y])
partial_fit_transform
Partially fits the model and then apply the transform to the data.
reset(self)
reset
Resets the estimator to its initial state.
set_params(self, **params)
set_params
Set the parameters of this estimator.
transform(self, X)
transform
Does the transformation process in the samples in X.
Configuration of the estimator.
If True, will return the parameters for this estimator and contained subobjects that are estimators.
Parameter names mapped to their values.
The sample or set of samples that should be transformed.
The target values.
self
The transformed data.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.
<component>__<parameter>