• Ensemble learning methods for decision making : status and future prospects 

      Ali, Shahid; Tirumala, Sreenivas Sremath; Sarrafzadeh, Hossein (Institute of Electrical and Electronics Engineers (IEEE), 2015-07)
      In real world situations every model has some weaknesses and will make errors on training data. Given the fact that each model has certain limitations, the aim of ensemble learning is to supervise their strengths and ...
    • A framework for evaluating anti spammer systems for Twitter 

      Ho, K.; Liesaputra, Veronica; Yongchareon, Dr. Sira; Mohaghegh, Dr Mahsa (Springer Verlag, 2017-10-20)
      Despite several benefits to modern communities and businesses, Twitter has attracted many spammers overwhelming legitimate users with unwanted and disruptive advertising and fake information. Detecting spammers is always ...
    • Tracking a person’s behaviour in a smart house 

      Chand, G.; Ali M.; Barmada, Bashar; Liesaputra, Veronica; Prado, G. (Springer Verlag, 2018-11)
      This paper proposes to use machine learning techniques with ultrasonic sensors to predict the behavior and status of a person when they live solely inside their house. The proposed system is tested on a single room. A grid ...

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