An Alternating Least Square Based Algorithm for Predicting Patient Survivability

Breast cancer is the most common cancer to females worldwide. Using machine learning technology to predict breast-cancer patients’ survivability has drawn a lot of research interest. However, it still faces many issues, such as missing-value imputation. As such, the main objective of this paper is to develop a novel imputation algorithm, inspired by the recommendation system. More precisely, features with missing values are regarded as items to be evaluated for recommendation.

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