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This repository contains the code necessary to reproduce the experiments described in the paper 'Effective Non-Random Extreme Learning Machine.'

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Effective Non-Random Extreme Learning Machine

This repository contains the Python code to reproduce the results of the paper "Effective Non-Random Extreme Learning Machine". Follow the instructions below to set up and run the code.

Table of Contents

Requirements

To ensure compatibility and proper functionality, use Python 3.10. Install the required Python packages as listed below:

  • numpy
  • scipy
  • matplotlib
  • scikit-learn

Install the packages using the following command:

pip install numpy scipy matplotlib scikit-learn

Preparing the Datasets

Before running the code, download the real datasets and place them in a folder named datasets. If this folder does not exist, create it manually.

Dataset Links

Download the datasets from the following links and organize them accordingly:

Generating Synthetic Datasets

Before running any experiments, it is recommended to execute datagenerator.py. This script will generate the synthetic datasets used in the experiments.

Run the following command:

python datagenerator.py

Running the Experiments

The repository includes two Jupyter notebooks:

  1. experiments.ipynb – This notebook runs the experiments and produces .csv files containing the results.
  2. presentation.ipynb – This notebook reads the results from experiments.ipynb and generates tables and plots for analysis.

Generating Zoomed Plots

To create a plot with zoom that displays training and test errors for all models on real datasets, run dynamicplot.py:

python dynamicplot.py

This interactive plot allows you to zoom in on a specified x-axis range, which is useful for detailed analysis and was used to create Figure 4 of the paper. If zooming is not required, you can produce the plot directly using presentation.ipynb.

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This repository contains the code necessary to reproduce the experiments described in the paper 'Effective Non-Random Extreme Learning Machine.'

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