Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...

This study presents a deep Convolutional Neural Network (CNN) model for automated COVID-19 RATD image classification. Methods: To address the absence of a RATD image dataset, we crowdsourced 900 ...

MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data Searching, retrieving, and arranging text in ever-larger document collections necessitate more efficient ...

This repository contains code and resources for performing multi-class classification on the CIFAR-10 dataset using transfer learning. Transfer learning is a powerful technique that leverages the ...

The experimental results demonstrate that the classification results of both centralized multi-person data fusion CNNs outperform the CNN classification results in single-person mode, and the four ...

Hence the team has devised a new method that combines classification problem data with multiple labels with the capacity to learn new things from data over time. The proposed method outperformed ...

Multi-class classification pipeline to predict earthquake damage as part of the Data Science Lab 2023 at KIT (Karlsruher Institute of Technology, Phase I. We won the internal course competition with ...

Dr. James McCaffrey of Microsoft Research: When multi-class data is skewed toward one or more classes, it's very important to analyze accuracy by class.