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International Journal of Machine Learning and Cybernetics

International Journal of Machine Learning and Cybernetics OnlineFirst articles

13.08.2018 | Original Article

An improvement to linear regression classification for face recognition

Linear regression classification (LRC) has attracted a great amount of attention owning to its promising performance in face recognition. However, its performance will dramatically decline in the scenario of limited training samples per class …

11.08.2018 | Original Article

Initial-training-free online sequential extreme learning machine based adaptive engine air–fuel ratio control

In modern automotive engines, air–fuel ratio (AFR) strongly affects exhaust emissions, power, and brake-specific consumption. AFR control is therefore essential to engine performance. Most existing engine built-in AFR controllers, however, are …

10.08.2018 | Original Article

A recommender system to address the Cold Start problem for App usage prediction

The Cold Start Recommender System (RS) for App usage prediction on mobile phones is important for improving new user experience on mobile operating systems. At present, the existing Cold Start RS computes the probability of App launching mainly by …

06.08.2018 | Original Article

F-WSS: incremental wrapper subset selection algorithm for fuzzy extreme learning machine

Fuzzy extreme learning machine (F-ELM) is a hybrid combination made to get the benefits of fuzzy system and extreme learning machine (ELM). F-ELM randomly initializes the weights between input layer to the hidden layer and analytically tunes the …

04.08.2018 | Original Article

Local dense mixed region cutting + global rebalancing: a method for imbalanced text sentiment classification

The category imbalance of data in text sentiment classification is a widely existent phenomenon, and it is a serious challenge for designing an effective classifier. In this paper, we propose a two-stage data balancing scheme for text sentiment …

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Über diese Zeitschrift

Cybernetics is concerned with describing complex interactions and interrelationships between systems which are omnipresent in our daily life. Machine Learning discovers fundamental functional relationships between variables and ensembles of variables in systems. The merging of the disciplines of Machine Learning and Cybernetics is aimed at the discovery of various forms of interaction between systems through diverse mechanisms of learning from data.

The International Journal of Machine Learning and Cybernetics (IJMLC) focuses on the key research problems emerging at the junction of machine learning and cybernetics and serves as a broad forum for rapid dissemination of the latest advancements in the area. The emphasis of IJMLC is on the hybrid development of machine learning and cybernetics schemes inspired by different contributing disciplines such as engineering, mathematics, cognitive sciences, and applications. New ideas, design alternatives, implementations and case studies pertaining to all the aspects of machine learning and cybernetics fall within the scope of the IJMLC.

Key research areas to be covered by the journal include:

  • Machine Learning for modeling interactions between systems
  • Pattern Recognition technology to support discovery of system-environment interaction
  • Control of system-environment interactions
  • Biochemical interaction in biological and biologically-inspired systems
  • Learning for improvement of communication schemes between systems
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