Classification is a complicated process that looks incredibly simple on the surface. Find out why classification matters in machine learning.

The predictive accuracy of 5 machine learning classifiers (logistic regression classifier, random forest classifier, support vector machine, k-nearest neighbor, and adaptive boosting) was examined ...

Beyond performance, the framework breaks new ground in its unification of symbolic reasoning and statistical learning.

Machine learning has revolutionised the field of classification in numerous domains, providing robust tools for categorising data into discrete classes.

The resulting classifier could identify tumor reactive T cells from TILs with 90% accuracy, works in many different types of tumor, and accommodates data from different cell sequencing technologies.

Machine learning classifier accelerates the development of cellular immunotherapies Date: March 15, 2024 Source: German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) Summary ...

Symbolic AI's adherents say it closely follows the logic of biological intelligence and analyzes symbols to arrive at intuitive conclusions.

The study provides both the theoretical foundations and empirical evidence for a new family of machine learning (ML) methods that not only compete with but outperform state-of-the-art statistical ...