Results 131 to 140 of about 5,507 (168)

C-ELM: A Curious Extreme Learning Machine for Classification Problems

2015
In psychology, curiosity is generally known as the critical intrinsic motivation for learning. It drives human beings to explore for novel and interesting information that can elicit the feeling of pleasure. This paper proposes such a curiosity driven algorithm for Extreme Learning Machine, which is referred to as Curious Extreme Learning Machine (C ...
Qiong Wu, Chunyan Miao
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MCK-ELM: multiple composite kernel extreme learning machine for hyperspectral images

Neural Computing and Applications, 2019
Multiple kernel (MK) learning (MKL) methods have a significant impact on improving the classification performance. Besides that, composite kernel (CK) methods have high capability on the analysis of hyperspectral images due to making use of the contextual information. In this work, it is aimed to aggregate both CKs and MKs autonomously without the need
Ugur Ergul, Gokhan Bilgin
openaire   +2 more sources

Using the Extreme Learning Machine (ELM) technique for heart disease diagnosis

2015 IEEE Canada International Humanitarian Technology Conference (IHTC2015), 2015
One of the most important applications of machine learning systems is the diagnosis of heart disease which affect the lives of millions of people. Patients suffering from heart disease have lot of independent factors such as age, sex, serum cholesterol, blood sugar, etc. in common which can be used very effectively for diagnosis.
Salam Ismaeel, Ali Miri, Dharmendra Chourishi   +2 more
openaire   +1 more source

ELM-ML: Study on Multi-label Classification Using Extreme Learning Machine

2016
Extreme learning machine (ELM) techniques have received considerable attention in computational intelligence and machine learning communities, because of the significantly low computational time. ELM provides solutions to regression, clustering, binary classification, multiclass classifications and so on, but not to multi-label learning. A thresholding
Xia Sun, Jiarong Wang, Changmeng Jiang, Jingting Xu, Jun Feng, Su-Shing Chen, Feijuan He   +6 more
openaire   +1 more source

ROS-ELM: A Robust Online Sequential Extreme Learning Machine for Big Data Analytics

2015
In this paper, a robust online sequential extreme learning machine (ROS-ELM) is proposed. It is based on the original OS-ELM with an adaptive selective ensemble framework. Two novel insights are proposed in this paper. First, a novel selective ensemble algorithm referred to as particle swarm optimization selective ensemble (PSOSEN) is proposed.
Yang Liu, Bo He, Diya Dong, Yue Shen, Tianhong Yan, Rui Nian, Amaury Lendasse   +6 more
openaire   +2 more sources

A-ELM⁎: Adaptive Distributed Extreme Learning Machine with MapReduce

Neurocomputing, 2016
Junchang Xin, Zhiqiong Wang, Luxuan Qu, Ge Yu, Yan Kang   +4 more
openaire   +1 more source

Prediksi Inflasi di Kota Bandung Menggunakan Metode Extreme Learning Machine (ELM)

Bandung Conference Series: Statistics
Abstract. This study aims to predict monthly inflation in Bandung City using the Extreme Learning Machine (ELM) method. Inflation, which is an indicator of economic stability, is important for predicting effective policy making. Data in the form of a time series of monthly inflation from January 2001 to March 2025 is used with a sliding window ...
null Hasan Al-Askary Kabalmay, Marizsa Herlina   +1 more
openaire   +1 more source

Microbial diversity in extreme environments

Nature Reviews Microbiology, 2021
Wen-Sheng Shu, Li-Nan Huang
exaly  

Ultra-high temperature ceramics for extreme environments

Nature Reviews Materials, 2023
Elizabeth
exaly  

Application of Extreme Learning Machine (ELM) Classification in Detecting Phishing Sites

2022 5th International Conference of Computer and Informatics Engineering (IC2IE), 2022
M. Rasyid Ridho, Hilal H. Nuha
openaire   +1 more source