Critical Evaluation of Machine Learning Research Aimed - IT Assignment Help

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Over the years, lie detection has gained interest across researches. The Polygraph technique, invented by John Augustus in 1921, has received critics across researches due to its inaccuracy and unscientific justification. Different methodologies have been researched as a way to come up with a much better technology to improve accuracy of the polygraph machine. This is to ensure that systems dependent on lie detection such as the legal systems, do not prosecute the innocent nor leave the guilt unprosecuted. This paper evaluates researches by different writers, to improve deception detection through machine learning. Conclusions pointed to the Electro-Encephalogram (EEG) Analysis standing a better chance at deception detection as it is not dependent on physiological reactions, but rather brain activity which is less likely to be influenced. The results lead to requiring more research to be carried out in order to improve the EEG technology for much finer results.


Introduction
Lie detection polygraphs became a topic of interest in legal systems to backup evidence when administering justice. According to Badhe (2016), its unreliability resulted in it not being approved in most courts of law. The State of California has recorded 17 ?ilure of the polygraph resulting in false conviction of suspects (Bonpasse 2013). However, Harne and Tale (2015) claim that, the polygraph is currently the most widely used technique, but have not given any statistical values to support the claims, making their claims quiet biased and questionable. Dayal (2014) stated that since the invention of the polygraph, its accuracy to detect deception has remained vigorously debated and has forced researchers to develop more accurate techniques. This was supported by Rajoub and Zwiggelaar (2014) who mentioned that thermal facial analysis technique has been studied by different researchers to improve deception detection. Tale and Harne (2014) also mentioned that other techniques have been investigated for deception detection e.g. Electro-Encephalogram Analysis (EEG) and Radar based lie detection.

 

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