About IJMLC

International Journal of Machine Learning and Computing (IJMLC) is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of machine learning and computing. The focus is to publish papers on state-of-the-art machine learning and computing. Submitted papers will be reviewed by technical committees of the Journal and Association. The audience includes researchers, managers and operators for machine learning and computing as well as designers and developers.

All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing.

Important Notice: IJMLC will only accept new submissions through online submission system


General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net

Editor-in-Chief

Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

Latest Articles

01Hand Gesture Detection Using Neural Networks Algorithms
N. Alnaim and M. Abbod

Abstract—Human gesture is a form of body language usually used as a mean of communication and is very critical in human-robot interactions Vision-based gesture recognition methods to [Click]

02A Machine Learning Approach: Using Predictive Analytics to Identify and Analyze High Risks Patients with Heart Disease
Fadoua Khennou, Charif Fahim, Habiba Chaoui, and Nour El Houda Chaoui

Abstract—The risk of developing early heart disease is always prominent In fact, according to the Central of Disease Control and Prevention (CDC), [Click]

03Autonomous UAV Navigation Using Reinforcement Learning
Mudassar Liaq and Yungcheol Byun

Abstract—Over the last few years, UAV applications have grown immensely from delivery services to military use. Major goal of UAV applications is to be able to operate and implement various tasks without any human aid.[Click]

04Memory Augmented Matching Networks for Few-Shot Learnings
Kien Tran, Hiroshi Sato, and Masao Kubo

Abstract—Despite many successful efforts have been made in one-shot/few-shot learning tasks recently, learning from few data remains one of the toughest areas in machine learning. [Click]

05Performance of Deep Neural Network for Tabular Data — A Case Study of Loss Cost Prediction in Fire Insurance
Dian Maharani, Hendri Murfi, and Yudi Satria

Abstract—The factors that influence fire insurance continue to grow and head to the problem of big data. It is necessary to develop a model to predict the loss cost due to fires by examining the state-of-art models which are adaptable to the big data.[Click]

06Illumination Correction in a Comparative Analysis of Feature selection for Rear-View Vehicle Detection
S. Baghdadi and N. Aboutabit

Abstract—One of the most frequent infractions on the road is the act of a vehicle crossing to the wrong side of the road to pass another vehicle traveling in the same direction. Automatic detection of this violation can be a challenging issue.[Click]

Most cited papers

01A Comparative Analysis of Nonlinear Machine Learning Algorithms for Breast Cancer Detection
Ali Al Bataineh

Abstract—Breast cancer is a form of invasive cancer and one of the most common health problems for women that is globally responsible for a large number of deaths Accurately classifying and categorizing breast cancer subtype is an essential task [Click]

02Predicting Scholarship Grants Using Data Mining Techniques
Allemar Jhone P. Delima

Abstract—Almost all major colleges and state universities assess students’ comprehensive quality and set different rewards and regulations for the various level in order to stimulate students’ interest to study and participate in [Click]

03Applying Data Mining Techniques in Predicting Index and non-Index Crimes
Allemar Jhone P. Delima

Abstract—An increasing incidence of crime has led to the development and use of computer-aided diagnosis system, tools and methods in analyzing, classifying and predicting crimes. This paper clusters municipalities in Surigao del Norte using [Click]

04Speaker Verification Using Deep Neural Networks: A Review
Amna Irum and Ahmad Salman

Abstract—Speaker verification involves examining the speech signal to authenticate the claim of a speaker as true or false. Deep neural networks are one of the successful implementation of complex non-linear models to learn unique and invariant [Click]

05Characteristics Identification of Myeloblast Cell Using K-Means Clustering for Uncontrolled Images
Retno Supriyanti, Ahmad Rifai, Yogi Ramadhani, and Wahyu Siswandari

Abstract—Blood cells are one of the most important parts in humans. One type of blood cells that play an important role in a leukemia diagnosis is leukocyte cells. [Click]

06Neural Networks to Predict Dropout at the Universities
Mayra Alban and David Mauricio

Abstract—The university student's dropout is a problem that affects the governments, institutions and students. It has negative effects on the high expenditure in the administrative and academic resources. [Click]

What's New

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