Machine learning is an integral part of high stakes decision making in a broad swath of human-computer interactions. You apply for a job. You submit a loan application. Algorithms determine who ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

Machine learning interview questions now focus on both theory and real-world applications.Understanding basics like overfitting, bias, and regres ...

Artificial intelligence models used to detect depression on social media are often biased and methodologically flawed, ...

Explainable machine learning models were used to identify predictive features, with SHapley Additive exPlanation (SHAP) analysis ranking variable importance. Two-way fixed-effect logistic regression ...

The paper bases on the theory of deep learning, uses the Scikit-learn machine learning framework and logistic regression algorithm, combines with supervised machine learning. Through Fourier transform ...

FinRegLab today released new empirical research demonstrating that adopting machine learning techniques and incorporating ...

To overcome these issues a hybrid model of eXtreme Gradient Boosting and Logistic Regression (XGBoost-LR) has proposed, which involves with preprocessing of Synthetic Minority Oversampling Technique ...