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An academic project to predict whether a breast cancer tumor is malignant or benign using logistic regression. Includes hyperparameter optimization with GridSearchCV.

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SantiagoMorenoV/Breast_Cancer_Logit_Model

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Breast Cancer Tumor Classification

Breast Cancer

Breast Cancer Tumor Classification

This project utilizes the Breast Cancer Wisconsin (Original) dataset to predict whether a breast cancer tumor is malignant or benign using a logistic regression model. The dataset contains features computed from digitized images of fine needle aspirates (FNA) of breast masses. This project aims to demonstrate the application of logistic regression as a classifier in data science, with potential applications in various fields, including medical diagnostics.

Logit Model

The logistic model can be accessed online via Binder at:

Binder

Chi-square Testing

Chi-square independence test can be accessed onlin via Binder at:

Binder

License

This project is licensed under the MIT License. See the LICENSE file for details.

References

Wolberg, W. (1990). Breast Cancer Wisconsin (Original) [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5HP4Z

Annex

I am new to working with Dash, but here are some of the results.

Binder

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An academic project to predict whether a breast cancer tumor is malignant or benign using logistic regression. Includes hyperparameter optimization with GridSearchCV.

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