Activation functions¶
-
statinf.ml.activations.
logit
(x, weights, bias=0, tensor=False)[source]¶ Logistic function
- Parameters
x (numpy.array) – Input value
weights (numpy.array) – Vector of weights \(\beta\)
bias (numpy.array) – Vector of bias \(\epsilon\), defaults to 0.
tensor (bool, optional) – Perform computation as tensor (theano type), defaults to False
- Returns
Logistic transformation: \(logit(x, \beta) = \dfrac{1}{1 + e^{-x \beta}}\)
- Return type
float
-
statinf.ml.activations.
relu
(x)[source]¶ Rectified Linear Units activation function
- Parameters
x (float or numpy.array) – Input value
- Returns
Activated value: \(relu(x) = \max(0, x)\)
- Return type
float
-
statinf.ml.activations.
sigmoid
(x)[source]¶ Sigmoid activation function
- Parameters
x (float or numpy.array) – Input value
- Returns
Sigmoid activated value: \(sigmoid(x) = \dfrac{1}{1 + e^{-x}}\)
- Return type
float