This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient ...

There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable in the ...

Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...

ABSTRACT: Burundi faces major agricultural constraints, including land fragmentation, soil erosion, limited access to inputs, inadequate infrastructure and demographic pressures that exacerbate food ...

Abstract: This study tries to detect fake job advertisements online using Novel Logistic Regression and compares its accuracy with linear regression. Data collection and model training are essential ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning ...

Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological ...