Use git clone to get a copy of this repository. Binary classification refers to those classification tasks that have two class labels, such as email spam detection (spam or not). Typically, binary ...

Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS) patients into four clinical profiles using structural connectivity information. For the first time, we try to solve ...

Mixed format tests (e.g., a test consisting of multiple-choice [MC] items and constructed response [CR] items) have become increasingly popular. However, the latent structure of item pools consisting ...

This paper develops a unified framework from Bayesian Decision Theory to address the problem of long-tailed classification. It unifies previous techniques like re-balancing loss and ensembling, and ...

With the recent developments of IoT technology, it has become relatively easy to obtain a large amount of data and use them for machine learning algorithms. Engaging in ongoing learning is becoming ...

Abstract: This study proposes a low-complexity interpretable classification system. The proposed system contains main modules including feature extraction, feature reduction, and classification. All ...

Abstract: Pattern classification based on Bayesian statistical decision theory needs a complete knowledge of the probability laws to perform the classification. In the actual pattern classification, ...