Package: Imneuron 0.1.0
Imneuron: AI Powered Neural Network Solutions for Regression Tasks
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.
Authors:
Imneuron_0.1.0.tar.gz
Imneuron_0.1.0.zip(r-4.5)Imneuron_0.1.0.zip(r-4.4)Imneuron_0.1.0.zip(r-4.3)
Imneuron_0.1.0.tgz(r-4.4-any)Imneuron_0.1.0.tgz(r-4.3-any)
Imneuron_0.1.0.tar.gz(r-4.5-noble)Imneuron_0.1.0.tar.gz(r-4.4-noble)
Imneuron_0.1.0.tgz(r-4.4-emscripten)Imneuron_0.1.0.tgz(r-4.3-emscripten)
Imneuron.pdf |Imneuron.html✨
Imneuron/json (API)
# Install 'Imneuron' in R: |
install.packages('Imneuron', repos = c('https://imiqbal.r-universe.dev', 'https://cloud.r-project.org')) |
- fruit - Fruit Characteristics
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 months agofrom:902b0d63b7. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Exports:Imneuron
Dependencies:bitopscaToolsclicolorspaceDerivfansifarverggplot2gluegplotsgtablegtoolsisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvMLmetricsmunsellneuralnetnlmepillarpkgconfigR6RColorBrewerrlangROCRscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Fruit Characteristics | fruit |
Fitting of AI based Neural Network Model | Imneuron |