Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Supervised machine learning problems are further divided into classification (predicting non-numeric answers, such as the probability of a missed mortgage payment) and regression (predicting ...

Dr. James McCaffrey of Microsoft Research uses code samples and screen shots to explain perceptron classification, a machine learning technique that can be used for predicting if a person is male or ...

Compared to other classification techniques, k-NN is easy to implement, supports numeric and categorical predictor variables, and is highly interpretable. By James McCaffrey; 10/01/2024; Multi-class ...

We apply clustering and machine learning techniques to analyze validation reports. The XGB oost model outperforms Logistic regression and clustering methods in predicting dimensions of findings from ...

As artificial intelligence (AI) and machine learning (ML) continue to advance, Linux has established itself as the preferred environment for AI development. Its open source nature, security, stability ...

Big Blue's quantum team has mathematically demonstrated that a quantum algorithm could work better than a classical one for machine-learning classification problems. Written by Daphne Leprince ...