Journal of Machine Learning Technologies (ISSN: 2229-3981)

Description

The journal focuses on the articles in advances in key compound classes and research areas of techniques of—
Any novel approaches Machine Learning Technologie
Accounts of applications of existing techniques that shed light on the strengths and weaknesses of the methods
Analogical learning methods
Application in pattern recognition, image understanding, control, robotics and bioinformatics
Application in system design, system identification, prediction, scheduling and game playing
Automated knowledge acquisition
Biochemical interaction in biological and biologically-inspired systems
Classification, regression, recognition, and prediction
Combinatorial optimization
Computational models of data from natural learning systems at the behavioral or neural level
Control of system-environment interactions
Data mining
Design and diagnosis
Development of new analytical frameworks that advance theoretical studies of practical learning methods
Different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications
Evolution-based methods
Experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems
Explanation-based learning
Extremely well-written surveys of existing work
Formalization of new learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks
Game playing
Industrial, financial, and scientific applications of all kinds
Information retrieval
Learning for improvement of communication schemes between systems
Learning from instruction
Learning in integrated architectures
Learning Problems
Machine Learning for modeling interactions between systems
Machine Learning on computational approaches to learning
Multi-agent learning
Multistrategy learning
Natural language processing
New algorithms with empirical, theoretical, psychological, or biological justification
Pattern Recognition technology to support discovery of system-environment interaction
Problem solving and planning
Reasoning and inference
Reinforcement learning
Robotics and control
Scientific discovery
Supervised and unsupervised learning methods (including learning decision and regression trees, rules, connectionist networks, probabilistic networks and other statistical models, inductive logic programming, case-based methods, ensemble methods, clustering, etc.)
Vision and speech perception
Visualization of patterns in data
Web mining

Journal of Machine Learning Technologies, ISSN: 2229-3981 & ISSN: 2229-399X, is an essential journal for all academic and industrial researchers who want expert knowledge on all major advances research areas in the Machine Learning.

The journal aims to provide the most complete and reliable source of information on current developments in the field. The emphasis will be on publishing quality articles rapidly and openly available to researchers worldwide. All published articles will be deposited immediately upon publication in widely and internationally recognized open access repository. Moreover, it is providing the maximum exposure to the articles.

The journal will be essential reading for scientists and researchers who wish to keep abreast of the latest developments in the field. The publishers are confident of the journal’s rapid success.


Bioinfo Journals are indexed in:
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