TimeSeriesClassificationActivationFunctions
Library "TimeSeriesClassificationActivationFunctions"
Provides some activation functions useful in time series classification.
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reference:
github.com/PYFTS/pyFTS/blob/master/pyFTS/common/Activations.py
method scale(dist, weights)
Activate values by a normalized scale.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: Normalized distribution map.
method softmax(dist, weights)
Activate values with a softmax algorithm.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: Normalized distribution map.
method argmax(dist, weights)
Activate values with a argmax algorithm.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: first key of argmax value of the transformed distribution.
Provides some activation functions useful in time series classification.
___
reference:
github.com/PYFTS/pyFTS/blob/master/pyFTS/common/Activations.py
method scale(dist, weights)
Activate values by a normalized scale.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: Normalized distribution map.
method softmax(dist, weights)
Activate values with a softmax algorithm.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: Normalized distribution map.
method argmax(dist, weights)
Activate values with a argmax algorithm.
Namespace types: map<int, float>
Parameters:
dist (map<int, float>): Source distribution map.
weights (map<int, float>): Weights distribution map.
Returns: first key of argmax value of the transformed distribution.
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Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.