https://github.com/makiato1999/esn

Machine Learning - Echo State Network
https://github.com/makiato1999/esn

python3

Last synced: about 2 months ago
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Machine Learning - Echo State Network

• Host: GitHub
• URL: https://github.com/makiato1999/esn
• Owner: Makiato1999
• Created: 2022-10-14T06:08:56.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-03-05T08:46:32.000Z (almost 2 years ago)
• Last Synced: 2024-11-13T14:04:35.121Z (about 2 months ago)
• Topics: python3
• Language: Jupyter Notebook
• Homepage:
• Size: 12.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# ESN-echo-state-network

simple standard echo state network

## Project specification

Implement a standard echo state network (ESN) model as discussed in class. Do not include feedback from the output and do not use leaky-integrator neurons. Implement training of the read-out weights by means of ridge regression. Perform experiments and comment the results by considering a _k_ step ahead forecasting task on the "2sine" and "lorentz" time series data provided to you together with this notebook. Evaluate the impact of relevant hyper-parameters on the results, including the reservoir size and the amount of training data used for optimizing the read-out weights. Finally, discuss the effects of using different forecasting horizons on the overall performance of the model.

### K step ahead forecasting

A _k_ step ahead forecasting task consists of predicting the value of a time series at time $t+k$ by using the value of the time series at time $t$, where $k\geq1$ is called forecasting horizon.

In general, the predicted value is always unidimensional (i.e. a single number). However, it is possible to use multiple input values in order to improve the results. Notably, once _k_ is decided, the output to be predicted is the value of the time series at time $t+k$, and the input may be a vector containing values of the times series at time $t, t-1, \dots, t-n$, where $n\geq0$ is defined by the user and sets the dimensionality of the input vector.

## Project Code and Report

Project is written by Python in Jupyter Lab, code and experiments are available here -> [Report](https://github.com/Makiato1999/ESN-echo-state-network/blob/main/project.ipynb)