IMPROVEMENT OF PREDICTION PERFORMANCE USING ASYMMETRIC TANH ACTIVATION FUNCTION

摘要

Provided is an asymmetric hyperbolic tanh function which can be used as an activation function irrespective of the structure of a neural network, according to one aspect of the present invention. The proposed activation function limits an output range thereof to between a maximum value and a minimum value of a variable to be predicted. The proposed activation function is suitable for a regression problem which requires the prediction of a wide range of real values on the basis of input data. Representative drawing: figure 3 Representative drawing: figure 3