---
license: cc-by-4.0
---

# Haberman's Survival Dataset

## Overview
This dataset contains tabular data for classifying survival status of patients who had undergone surgery for breast cancer. 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:
Haberman-Survival/
    train_data/
        class_1/
            sample_0.txt
            sample_10.txt
            ...
        class_2/
            sample_0.txt
            sample_10.txt
            ...
    test_data/
        class_1/
            sample_0.txt
            sample_10.txt
            ...
        class_2/
            sample_0.txt
            sample_10.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 two classes, each represented by a separate folder:
    - `class_1`: Patients who survived 5 years or longer.
    - `class_2`: Patients who did not survive 5 years.

## Usage(pre-split; optimal parameters)
Here is an example of how to load the dataset using PrismRCL:

```bash
C:\PrismRCL\PrismRCL.exe naivebayes rclticks=18 boxdown=1 channelpick=5 data=C:\path\to\Haberman-Survival\train_data testdata=C:\path\to\Haberman-Survival\test_data savemodel=C:\path\to\models\mymodel.classify log=C:\path\to\log_files stopwhendone

Explanation of Command

  C:\PrismRCL\PrismRCL.exe: classification application
  chisquared: training evaluation method
  rclticks=18: RCL training parameter
  boxdown=1: RCL training parameter
  channelpick=5 : RCL training parameter
  data=C:\path\to\Haberman-Survival\train: path to training data
  testdata=C:\path\to\Haberman-Survival\test: path to testing data
  savemodel=C:\path\to\models\mymodel.classify: path to save resulting model
  log=C:\path\to\log_files: path to logfiles
  stopwhendone: ends the PrismRCL session when training is done
```

## 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 [UCI Machine Learning Repository](https://archive.ics.uci.edu/dataset/43/haberman+s+survival). Please cite the original source if you use this dataset in your research or applications.

```
Haberman, S.J. (1976). Generalized Residuals for Log-Linear Models. Proceedings of the 9th International Biometrics Conference, Boston, 1976.
```

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