Backpropagation-based Multi Layer Perceptron Neural Networks

Version 1.2 (1,07 Mo) par Shujaat Khan
Backpropagation-based Multi Layer Perceptron Neural Networks (MLP-NN) for the classification
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Mise à jour 28 avr. 2020

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%% Backpropagation for Multi Layer Perceptron Neural Networks %%
% Author: Shujaat Khan,
% cite:
% @article{khan2018novel,
% title={A Novel Fractional Gradient-Based Learning Algorithm for Recurrent Neural Networks},
% author={Khan, Shujaat and Ahmad, Jawwad and Naseem, Imran and Moinuddin, Muhammad},
% journal={Circuits, Systems, and Signal Processing},
% volume={37},
% number={2},
% pages={593--612},
% year={2018},
% publisher={Springer US}
% }
%% Description
% In this simulation I used a Golub et al(1999)'s Leukemia Cancer Database.
% The details of the dataset is available online at [1]. The leukemia db
% is a gene expression dataset contains 7128 genes, 2-classes (47-ALL &
% 25-AML), divided into two subsets training and test subsets. The training
% dataset contains 27-ALL, and 11-AML total 38 samples, and the test subset
% contains 20-ALL, and 14-AML total 34 samples.
% The genes are ranked using mRMR feature selection method [2] and the
% index of top 1000 genes is stored in 'feature_with_mRMr_d' vector.
% [1]
% [2]

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Shujaat Khan (2024). Backpropagation-based Multi Layer Perceptron Neural Networks (, MATLAB Central File Exchange. Récupéré le .

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