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license: cc-by-4.0

Wheat Seeds Dataset

Overview

This dataset contains tabular data for classifying different varieties of wheat seeds. Each sample is stored in a separate text file, with features space-separated on a single line. The dataset is structured to be compatible with Lumina AI's Random Contrast Learning (RCL) algorithm via the PrismRCL application or API.

Dataset Structure

The dataset is organized into the following structure:

Wheat-Seeds/
    train_data/
        class_1/
            sample_0.txt
            sample_1.txt
            ...
        class_2/
            sample_0.txt
            sample_1.txt
            ...
        class_3/
            sample_0.txt
            sample_1.txt
            ...
    test_data/
        class_1/
            sample_0.txt
            sample_1.txt
            ...
        class_2/
            sample_0.txt
            sample_1.txt
            ...
        class_3/
            sample_0.txt
            sample_1.txt
            ...

Note: All text file names must be unique across all class folders.

Features

  • Tabular Data: Each text file contains space-separated values representing the features of a sample.
  • Classes: There are three classes, each represented by a separate folder.

Thank you for providing the command and its explanation. I'll ensure that the 'usage' section is consistent with the included command. Here's a revised version of the usage section:

Usage (pre-split; optimal parameters)

Here is an example of how to load the dataset using PrismRCL:

C:\PrismRCL\PrismRCL.exe naivebayes rclticks=7 boxdown=0 channelpick=5 data=C:\path\to\Wheat-Seeds\train_data testdata=C:\path\to\Wheat-Seeds\test_data savemodel=C:\path\to\models\mymodel.classify log=C:\path\to\log_files stopwhendone

Explanation of Command:

  • C:\PrismRCL\PrismRCL.exe: Path to the PrismRCL executable for classification
  • naivebayes: Specifies Naive Bayes as the training evaluation method
  • rclticks=7: Sets the number of RCL iterations during training to 7
  • boxdown=0: RCL training parameter
  • channelpick=5: RCL training parameter
  • data=C:\path\to\Wheat-Seeds\train_data: Path to the training data for wheat seeds classification
  • testdata=C:\path\to\Wheat-Seeds\test_data: Path to the testing data for evaluation
  • savemodel=C:\path\to\models\mymodel.classify: Path to save the resulting trained model
  • log=C:\path\to\log_files: Directory path for storing log files of the training process
  • stopwhendone: Instructs PrismRCL to end the session once training is complete

This usage section now accurately reflects the provided command and includes a consistent explanation for each parameter.

License

This dataset is licensed under the Creative Commons Attribution 4.0 license. See the LICENSE file for more details.

Original Source This dataset was originally sourced from the UCI Machine Learning Repository. Please cite the original source if you use this dataset in your research or applications. Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [https://archive.ics.uci.edu/dataset/236/seeds]. Irvine, CA: University of California, School of Information and Computer Science.


## Additional Information
The data values have been prepared to ensure compatibility with PrismRCL. No normalization is required as of version 2.4.0.