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 ...
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
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