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Imneuron
View on CRAN: Click
here
Download and install Imneuron package within the R console
Install from CRAN:
install.packages("Imneuron")
Install from Github:
library("remotes")
install_github("cran/Imneuron")
Install by package version:
library("remotes")
install_version("Imneuron", "0.1.0")
Attach the package and use:
library("Imneuron")
Maintained by
M Iqbal Jeelani
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-06-20
Latest Update: 2024-06-20
Description:
It offers a sophisticated and versatile tool for creating and evaluating artificial intelligence based neural network models tailored for regression analysis on datasets with continuous target variables. Leveraging the power of neural networks, it allows users to experiment with various hidden neuron configurations across two layers, optimizing model performance through "5 fold"" or "10 fold"" cross validation. The package normalizes input data to ensure efficient training and assesses model accuracy using key metrics such as R squared (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Percentage Error (PER). By storing and visualizing the best performing models, it provides a comprehensive solution for precise and efficient regression modeling making it an invaluable tool for data scientists and researchers aiming to harness AI for predictive analytics.
How to cite:
M Iqbal Jeelani (2024). Imneuron: AI Powered Neural Network Solutions for Regression Tasks. R package version 0.1.0, https://cran.r-project.org/web/packages/Imneuron. Accessed 21 Nov. 2024.
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