Abstract: K-fold cross-validation is a widely used tool for assessing classifier performance. The reproducibility crisis [6] faced by artificial intelligence partly results from the irreproducibility ...

Abstract: With the rapid development of digital technology, people increasingly use images to express and convey information, and image classification, as a core problem in the image field, has shown ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...

Derive the Equations for the Backpropagation for Softmax and Multi-class Classification. In this video, we will see the ...

Institute for Information Systems (WIN), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany Introduction: The analysis of discrete sequential data, such as event logs and customer ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

This study presents data on sex differences in gene expression across organs of four mice taxa. The authors have generated a unique and convincing dataset that fills a gap left by previous studies.

The Large-ness of Large Language Models (LLMs) ushered in a technological revolution. We dissect the research. The Large-ness of Large Language Models (LLMs) ushered ...

This repository contains two basic prediction models: Credit Card Fraud Detection and Titanic Survival Prediction. Both models demonstrate the use of machine learning for binary classification tasks.

In this study, we propose a novel modularized Quantum Neural Network (mQNN) model tailored to address the binary classification problem on the MNIST dataset. The mQNN organizes input information using ...