Researchers examined data from 117,000 men with Grade Group one tumors and discovered that many required more aggressive treatments than their initial classification suggested.

For two different problem frameworks typical in forensic science, the common source and the specific source problems, we show the Bayes Factor and likelihood ratio are not equivalent, and highlight ...

Brownlee, J. (2017) Difference between Classification and Regression in Machine Learning. Machine Learning Mastery, 25, 981-985.

The Data Science Lab Regression Using LightGBM Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a ...

If there is high agreement between the two – in the best case, perfect agreement – the machine is approaching human-level common sense, according to the test. So where would noise come in?

Therefore, the speed and performance of classification could be greatly affected. Given the above problems, this paper starts with the motivation and mathematical representing of classification, puts ...

In order to enhance the generalization ability of the IBWO-RBF neural network, the algorithm is designed with nonlinear time-varying inertia weight. Discussion: Several classification and regression ...

This article proposes an algorithm for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The resulting ...