As a new machine learning approach, the extreme learning machine (ELM) has received much attention due to its good performance. However, when directly applied to hyperspectral image (HSI) classification, the recognition rate is low. This is because ELM does not use spatial information, which is very important for HSI classification. In view of this, this paper proposes a new framework for the s...

Extreme learning machine (ELM) has shown its good performance in regression applications with a very fast speed. But there is still a difficulty to compromise between better generalization performance and smaller complexity of the ELM (number of hidden nodes). This paper proposes a method called Delta TestELM (DT-ELM), which operates in an incremental way to create less complex ELM structures a...

The aim of this study is to explore the various diagnostic techniques for melanoma and assess their usefulness in the clinical practice of nurse practitioners. After a systematic review of the literature, 55 articles were closely reviewed, and from these, 26 studies were selected. These were original studies in English that examined diagnostic techniques that would improve accuracy for melanoma...

An emerging business model, known as Electronic Logistics Marketplace (ELM), is increasingly being recognised for its potential to address the issue of poor vehicle utilisation. This research investigates the feasibility of setting up a neutral government-supported regional ELM which will fully exploit the potential of such a collaborative network across industries and achieve transport optimis...

In recent years, the interest in the study of outlier robustness properties in Extreme Learning Machines (ELM) has grown. Most of the published works uses a more robust estimation method than the commonly adopted ordinary least squares. Nevertheless, the ELM network offers other challenges that also influence its robustness properties, such as the number of hidden neurons and the computational ...

Little is known about the associations of eating a late-evening meal (ELM), a putative unhealthy eating behavior, with low serum amylase, other eating behaviors, and cardiometabolic risk factors. Therefore, we investigated whether ELM before bedtime was associated with low serum amylase or other clinical factors in 2,426 asymptomatic adults aged 20-80 years. Multivariate logistic regression ana...

In this paper, a new hidden layer construction method for Extreme Learning Machines (ELMs) is investigated, aimed at generating a diverse set of weights. The paper proposes two new ELM variants: Binary ELM, with a weight initialization scheme based on f0;1g–weights; and Ternary ELM, with a weight initialization scheme based on f 1;0;1g–weights. The motivation behind this approach is that these ...

A new learning algorithm called extreme learning machine (ELM) has recently been proposed for single-hidden layer feedforward neural networks (SLFNs) with additive neurons to easily achieve good generalization performance at extremely fast learning speed. ELM randomly chooses the input weights and analytically determines the output weights of SLFNs. It is proved in theory that ELM can be extend...

BACKGROUND The accuracy of digital epiluminescence microscopy (D-ELM) as an adjunct to clinical examination for the diagnosis of pigmented skin lesions (PSLs) has seldom been evaluated. OBJECTIVE To compare the accuracy of the combined clinical/D-ELM (C/D-ELM) examination with that of the clinical examination alone. METHODS A total of 3,372 PSLs from 1,556 consecutive patients referred to a...

This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as “online RK-OC-ELM”. The baseline kernel hyperplane model considers whole data in a single chunk with regularized ELM approach for offline learning in case of one-class classification (OCC). Further, the basic hyper plane model is adapted in an online fashio...