Breast cancer prediction using machine learning algorithms

HIGHLIGHTS

• What: By leveraging both continuous and discrete datasets the authors compare the predictive accuracy and error rates of these algorithms. The authors evaluate their performance based on accuracy, precision, recall, and other metrics to determine the most suitable algorithm for early breast cancer detection. The aims of this study are: To compare the predictive accuracy of Artificial_Neural_Networks (ANN) and Naïve Bayes (NB) in classifying breast cancer data.
• Who: Dell from the (UNIVERSITY) have published the Article: International Journal for Multidisciplinary Research (IJFMR), in the Journal: (JOURNAL)
• How: This data was encoded using . . .
  

   

  

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