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Label-Noise Resistant Logistic Regression for Functional Data Classification with an Application to Alzheimer's Disease Study

Alzheimer's disease (AD) is usually diagnosed by clinicians through cognitive and functional performance test with a potential risk of misdiagnosis. Since the progression of AD is known to cause ...
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Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

A total of 737 treatment-naïve patients with CLL diagnosed at Mayo Clinic were included in this study. We compared predictive abilities for two survival models (Cox proportional hazards and random ...
JSTOR Daily

Tuning Data Mining Methods for Cost-Sensitive Regression: A Study in Loan Charge-Off Forecasting

Real-world predictive data mining (classification or regression) problems are often cost sensitive, meaning that different types of prediction errors are not equally costly. While cost-sensitive ...
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Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...