Random Sample Expands Its Footprint — and Its Vision The beloved local gallery and music venue has relocated to a bigger space on Charlotte Avenue ...

Multiple classification models including Logistic Regression, Linear SVM, and Random Forest were trained and evaluated. Among them, XGBoost performed best, achieving high accuracy and balanced ...

As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural Network (CNN ...

Black Forest Labs has launched FLUX.1 Kontext, its new AI model suite offering advanced in-context image generation and editing with claims of significantly faster speeds, aiming to enhance ...

Fake Instagram Account Detection using Random Forest This project implements a machine learning-based solution to detect fake Instagram accounts using Random Forest classification. The system analyzes ...

Black Forest Labs, the AI startup whose models once powered the image generation features of X's Grok chatbot, has released a new suite of image-generating models — some of which can both create ...

Then, the random forest, classification regression tree (CART) and gradient Lift Tree (GBT) classification algorithms were used to compare the models. The results showed that the random forest ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

Then, the random forest, classification regression tree (CART) and gradient Lift Tree (GBT) classification algorithms were used to compare the models. The results showed that the random forest ...

Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR ...