Quantum algorithm beats classical tools on complement sampling tasks

Quantum computers—devices that process information using quantum mechanical effects—have long been expected to outperform ...

Lab-grown brain tissue successfully solves a classic AI training problem

In a small lab at the University of California, Santa Cruz, clusters of mouse brain cells have taken on a task normally reserved for computer algorithms: ...
IEEE

Comparison of Novel Random Forest Algorithm over Gaussian Naïve Bayes for Improving Accuracy in Software Bug Prediction System

Abstract: Aim: This research work focuses on analyzing the performance of a proposed random forest method with that of Gaussian Naive Bayes in predicting software problems. Materials and Methods: The ...
IEEE

A Multi-Algorithm Stacking Approach to Lung Cancer Detection with SVM, GBM, Naive Bayes, Decision Tree, and Random Forest Models

Abstract: Lung health is one of the most minor medical issues globally because of its low mortality rate and high chance of early detection. The model presented here is a multi-model design that uses ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...