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license: cc-by-4.0 |
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# Haberman's Survival Dataset |
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## Overview |
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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. |
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## Dataset Structure |
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The dataset is organized into the following structure: |
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Haberman-Survival/ |
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train_data/ |
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class_1/ |
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sample_0.txt |
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sample_10.txt |
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... |
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class_2/ |
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sample_0.txt |
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sample_10.txt |
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... |
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test_data/ |
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class_1/ |
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sample_0.txt |
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sample_10.txt |
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... |
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class_2/ |
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sample_0.txt |
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sample_10.txt |
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... |
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**Note**: All text file names must be unique across all class folders. |
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## Features |
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- **Tabular Data**: Each text file contains space-separated values representing the features of a sample. |
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- **Classes**: There are two classes, each represented by a separate folder: |
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- `class_1`: Patients who survived 5 years or longer. |
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- `class_2`: Patients who did not survive 5 years. |
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## Usage (pre-split; optimal parameters) |
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Here is an example of how to load the dataset using PrismRCL: |
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```bash |
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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 |
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``` |
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Explanation of Command: |
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- `C:\PrismRCL\PrismRCL.exe`: Path to the PrismRCL executable for classification |
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- `naivebayes`: Specifies Naive Bayes as the training evaluation method |
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- `rclticks=18`: Sets the number of RCL iterations during training to 18 |
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- `boxdown=1`: Configuration parameter for training behavior |
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- `channelpick=5`: RCL training parameter |
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- `data=C:\path\to\Haberman-Survival\train_data`: Path to the training data for Haberman Survival classification |
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- `testdata=C:\path\to\Haberman-Survival\test_data`: Path to the testing data for evaluation |
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- `savemodel=C:\path\to\models\mymodel.classify`: Path to save the resulting trained model |
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- `log=C:\path\to\log_files`: Directory path for storing log files of the training process |
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- `stopwhendone`: Instructs PrismRCL to end the session once training is complete |
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## License |
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This dataset is licensed under the Creative Commons Attribution 4.0 International License. See the LICENSE file for more details. |
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## Original Source |
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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. |
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``` |
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Haberman, S.J. (1976). Generalized Residuals for Log-Linear Models. Proceedings of the 9th International Biometrics Conference, Boston, 1976. |
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``` |
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## Additional Information |
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The data values have been prepared to ensure compatibility with PrismRCL. No normalization is required as of version 2.4.0. |
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