3.2. Machine Learning Models Three machine learning models were implemented for classification: 1) Logistic Regression (LR): A linear classifier that predicts the likelihood of CHD based on input ...

Automatic bug assignment has been well studied in the past decade. As textual bug reports usually describe the buggy phenomena and potential causes, engineers highly depend on these reports to fix ...

Data mining algorithms play a vital role to predict the early stage cancer .The research problem is that there are lots of classifier with different level of accuracy. An approach for improving the ...

However, previous studies mainly focus on brain disease classification in small sample sizes, which may lead to dramatic divergences in classification accuracy. Methods: This paper attempts to address ...

Binary Classification Using New PyTorch Best Practices, Part 2: Training, Accuracy, Predictions Dr. James McCaffrey of Microsoft Research explains how to train a network, compute its accuracy, use it ...

Keywords: bit-fusion ensemble algorithm, classifier fusion, k-nearest neighbor, Multi-Layer Perceptron, Naïve Bayesian classifier, support vector machine Citation: Mishra S, Shaw K, Mishra D, Patil S, ...

A support vector machine (SVM) is a software system that can perform binary classification. For example, you can use an SVM to create a model that predicts the sex of a person (male, female) based on ...

Recently, LSTSVM as a new binary SVM classifier based on nonparallel twin hyperplanes has shown a good classification performance, but the research on multi-class classification has still rarely been ...