NeuralSens - Sensitivity Analysis of Neural Networks
Analysis functions to quantify inputs importance in neural network models. Functions are available for calculating and plotting the inputs importance and obtaining the activation function of each neuron layer and its derivatives. The importance of a given input is defined as the distribution of the derivatives of the output with respect to that input in each training data point <doi:10.18637/jss.v102.i07>.
Last updated 5 months ago
5.53 score 15 stars 25 scripts 382 downloadsTSLSTMplus - Long-Short Term Memory for Time-Series Forecasting, Enhanced
The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network (RNN) based architecture that is widely used for time series forecasting. Customizable configurations for the model are allowed, improving the capabilities and usability of this model compared to other packages. This package is based on 'keras' and 'tensorflow' modules and the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.
Last updated 17 days ago
3.30 score 1 scripts 364 downloads