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Research Article
Vol. 1, Issue 1
Evaluating the effect of feature scaling on L2-regularized logistic regression for breast cancer classification
Feature scaling is a common preprocessing technique in machine learning but its effect depends on the scaling strategy and the type of data used. In this paper, a performance test of L2-regularized Logistic Regression was carried out on breast cancer classification, based on three feature-scaling conditions, namely, no scaling, Min--Max scaling, an...