---
license: cc-by-4.0
---
# Ecommerce Product Descriptions Dataset

## Overview
This dataset contains product descriptions for various ecommerce products. 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:

Ecommerce_Product_Descriptions/
  train_data/
    category_1/
      sample_0.txt
      sample_1.txt
      ...
    category_2/
      sample_0.txt
      sample_1.txt
      ...
  test_data/
    category_1/
      sample_0.txt
      sample_1.txt
      ...
    category_2/
      sample_0.txt
      sample_1.txt
      ...

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

## Features
- **Tabular Data**: Each text file contains space-separated values representing the features of a sample.
- **Categories**: There are multiple categories, each represented by a separate folder based on the type of product.

## Usage (not pre-split; optimal parameters)
Here is an example of how to load the dataset using PrismRCL:
```bash
C:\PrismRCL\PrismRCL.exe chisquared rclticks=65 boxdown=8 channelpick=5 data=C:\path\to\Ecommerce_Product_Descriptions_mm testsize=0.1 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
- `chisquared`: Specifies Chi-squared as the training evaluation method
- `rclticks=65`: Sets the number of RCL iterations during training to 65
- `boxdown=8`: Configuration parameter for training behavior
- `channelpick=5`: RCL training parameter
- `data=C:\path\to\Ecommerce_Product_Descriptions_mm`: Path to the complete dataset for Ecommerce Product Descriptions classification
- `testsize=0.1`: Specifies that 10% of the data should be used for testing
- `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

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

## Original Source
This dataset was originally sourced from the [Kaggle Dataset Repository](https://www.kaggle.com/datasets/saurabhshahane/ecommerce-text-classification). Please cite the original source if you use this dataset in your research or applications.

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