They help determine if a model is truly learning or just memorizing Mathematics In AI: Mathematical concepts such as statistics and probability form the foundation of Artificial Intelligence (AI) and ...

Joshi, R.D. and Dhakal, C.K. (2021) Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches. International Journal of Environmental Research and Public Health, 18, Article ...

Scientists in Australia have developed a quantum machine learning technique — a blend of artificial intelligence (AI) and quantum computing principles — that could change how microchips are made.

Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine learning ...

Logistic regression is an approach to supervised machine learning that models selected values to predict possible outcomes. In this course, Notre Dame professor Frederick Nwanganga provides you with a ...

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 ...

The results are further evaluated by selective sampling and tuning, and improved performance is observed. The precision and accuracy obtained by the support vector machine and artificial neural ...