Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability.
João Manoel Herrera PinheiroMarcelo BeckerPublished in: CoRR (2024)
Keyphrases
- breast cancer
- false negative
- false positives
- breast cancer diagnosis
- bladder cancer
- mammogram images
- boosting algorithms
- cost sensitive
- breast tissue
- logistic regression
- benchmark datasets
- classification accuracy
- feature space
- false positive rate
- text classification
- decision trees
- weak classifiers
- detection rate
- supervised learning
- image classification
- machine learning methods
- generalization error
- binary classification
- binary classifiers
- naive bayes
- learning algorithm
- support vector machine
- machine learning
- class labels
- loss function
- feature vectors
- support vector
- computer vision