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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Clause de non-responsabilité
Les informations et publications ne sont pas destinées à être, et ne constituent pas, des conseils ou recommandations financiers, d'investissement, de trading ou autres fournis ou approuvés par TradingView. Pour en savoir plus, consultez les Conditions d'utilisation.