Prasun Chaudhuri speaks to expert Subrata Das about the opportunities. Das is currently an adjunct faculty member at ...

Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania.

Digital finance is accelerating, and threats are evolving in complexity, outpacing traditional methods for detecting fraud.

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 ...

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model. It shows how the ...

The accurate and early detection of coronary heart disease (CHD) is crucial for reducing mortality rates. This study evaluates the predictive performance of three machine learning models—Logistic ...

Linear regression vs logistic regression. Linear regression in machine learning. ... Due to the simple and interpretable nature of the model, linear regression has become a fundamental machine ...

There are dozens of machine learning algorithms, ranging in complexity from linear regression and logistic regression to deep neural networks and ensembles (combinations of other models). However ...