Updated
FunctionNNLayer
Library "FunctionNNLayer"
Generalized Neural Network Layer method.
function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer.
Parameters:
inputs: float array, input values.
weights: float array, weight values.
n_nodes: int, number of nodes in layer.
activation_function: string, default='sigmoid', name of the activation function used.
bias: float, default=1.0, bias to pass into activation function.
alpha: float, default=na, if required to pass into activation function.
scale: float, default=na, if required to pass into activation function.
Returns: float
Generalized Neural Network Layer method.
function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer.
Parameters:
inputs: float array, input values.
weights: float array, weight values.
n_nodes: int, number of nodes in layer.
activation_function: string, default='sigmoid', name of the activation function used.
bias: float, default=1.0, bias to pass into activation function.
alpha: float, default=na, if required to pass into activation function.
scale: float, default=na, if required to pass into activation function.
Returns: float
Release Notes
v2 Support for matricesUpdated:
function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer.
Parameters:
inputs: float array, input values.
weights: float matrix, weight values.
n_nodes: int, number of nodes in layer.
activation_function: string, default='sigmoid', name of the activation function used.
bias: float, default=1.0, bias to pass into activation function.
alpha: float, default=na, if required to pass into activation function.
scale: float, default=na, if required to pass into activation function.
Returns: float
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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.