26 research outputs found
Recommended from our members
Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP
During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as Mitchell’s, tended to use a one-dimensional approach to Machine Learning based solely on predictive accuracy, ultimately favouring statistical over symbolic Machine Learning approaches. In this paper we provide a definition of comprehensibility of hypotheses which can be estimated using human participant trials. We present two sets of experiments testing human comprehensibility of logic programs. In the first experiment we test human comprehensibility with and without predicate invention. Results indicate comprehensibility is affected not only by the complexity of the presented program but also by the existence of anonymous predicate symbols. In the second experiment we directly test whether any state-of-the-art ILP systems are ultra-strong learners in Michie’s sense, and select the Metagol system for use in humans trials. Results show participants were not able to learn the relational concept on their own from a set of examples but they were able to apply the relational definition provided by the ILP system correctly. This implies the existence of a class of relational concepts which are hard to acquire for humans, though easy to understand given an abstract explanation. We believe improved understanding of this class could have potential relevance to contexts involving human learning, teaching and verbal interaction
Developing and integrating theory on school bullying
Given the number of factors involved in bullying, the range ofexplanatory theory upon which one might draw is vast. Not only might one consider factors within the family, the individual, the peer group, the school and the community, but each of these could be considered from a number of different perspectives. This paper explores the issues for both the individual practitioner/researcher and for the field as a whole in developing and integrating theory in relation to school bullying. Interviews with 11 psychologists expert in the field of school bullying discussed their opinions about the current public body of knowledge and their personal approach to developing a personal understanding of bullying. The findings are organised within a problem solving framework
Screen as Skin: The Somatechnics of Touchscreen Music Media
In this article I explore the way mobile music devices with touchscreen technology produce new somatechnical figurations that reshape emotional dynamics of music listening. Using research drawn from a cyberethnography of online users from Reddit.com, I argue that the changing relationships between the human-computer interface result in new affective schemas that expand and reconfigure how it feels to listen to music in a mobile setting. In particular, I focus on skin-on-screen contact in order to suggest that the screen acts as a reflexive surface producing intimate relations for the mobile listener. Touchscreens imply the relationship between skin on skin—the skin of our body (in particular the hands) against the skin of the screen. It follows that mobile touchscreen devices suggest a degree of sensuality—in the coming together of bodies, fluids and other organic materials which ‘stick’ to the touchscreen. Reading the mobile touchscreen player as a somatechnical figuration therefore suggests that the listening experience is developing along with the technologies that mediate music to the body in ways that continue to challenge our understanding of bodily borders and in ways that redefine what it means to feel the music. Therefore, the touchscreen-skin is a critical site of affective relations that dramatically reshape what it means to listening to music in a mobile setting; a private and intimate encounter between the user and their counterpart