The performance of regression methods for selecting the best individuals was compared with that of three supervised classification algorithms: Random Forest Classification (RFC) and Support Vector ...

The first job for many artificial intelligence (AI) algorithms is to examine the data and find the best classification. An autonomous car, for example, may take an image of a street sign; the ...

Besides the well-known classification algorithms (eg logistic regression, discriminant analysis, k-nearest neighbour, neural networks and decision trees), this study also investigates the suitability ...

CHUNMING ZHANG, YUAN JIANG, YI CHAI, Penalized Bregman divergence for large-dimensional regression and classification, Biometrika, Vol. 97, No. 3 (SEPTEMBER 2010), pp. 551-566 ...

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams. Authors: ... Our central finding is that LR ...

Summary: Ink authentication is often complicated by tampering, aging, and chemical variability. Now, forensic scientists are ...

Because of this, k-NN classification is often best used as part of an ensemble approach to validate other classification algorithms. For example, you could predict using a logistic regression model ...