Predicting breast cancer biopsy outcomes from BI-RADS findings using random forests with chi-square and MI features.
Sheldon WilliamsonK. VijayakumarVinod Jagannath KadamPublished in: Multim. Tools Appl. (2022)
Keyphrases
- breast cancer
- logistic regression
- chi square
- random forests
- mammogram images
- support vector
- decision trees
- naive bayes
- mutual information
- information gain
- feature set
- image features
- feature vectors
- co occurrence
- loss function
- random forest
- feature extraction
- benchmark datasets
- ensemble methods
- machine learning algorithms
- training data
- cancer patients
- data mining