منابع مشابه
Double Deep Machine Learning
Very important breakthroughs in data-centric machine learning algorithms led to impressive performance in ‘transactional’ point applications such as detecting anger in speech, alerts from a Face Recognition system, or EKG interpretation. Nontransactional applications, e.g. medical diagnosis beyond the EKG results, require AI algorithms that integrate deeper and broader knowledge in their proble...
متن کاملAfterhyperpolarization of human motoneurons firing double and triple discharges
INTRODUCTION During isometric voluntary contractions of a healthy human muscle, motoneurons (MNs) fire usually with low mean rates, rarely exceeding 25/s (e.g., Garland and Griffin, 1999). However, there are MNs, which sometimes fire double discharges (doublets) with interspike interval (ISI) of few ms. This is observed seldom in normal MNs (e.g., Denslow, 1948; Kudina, 1974; Bawa and Calancie,...
متن کاملThe Influence of Machine Parameters on the Properties of Double Jersey Knitted Fabrics
The present work is an experimental account of the way in which several machine settings, particularly cylinder knock-over and dial-height, influence fabric dimensions, course length, bending behavior and load extension of fabrics produced on a circular knitting machine. The results show that there are certain optimum settings for such variables as knock-over depth and dial-height for producing...
متن کاملMachine learning bandgaps of double perovskites
The ability to make rapid and accurate predictions on bandgaps of double perovskites is of much practical interest for a range of applications. While quantum mechanical computations for high-fidelity bandgaps are enormously computation-time intensive and thus impractical in high throughput studies, informatics-based statistical learning approaches can be a promising alternative. Here we demonst...
متن کاملDouble SVMBagging: A New Double Bagging with Support Vector Machine
In ensemble methods the aggregation of multiple unstable classifiers often leads to reduce the misclassification rates substantially in many applications and benchmark classification problems. We propose here a new ensemble, “Double SVMBagging”, which is a variant of double bagging. In this ensemble method we used the support vector machine as the additional classifiers, built on the out-of-bag...
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ژورنال
عنوان ژورنال: British Journal of Psychiatry
سال: 1993
ISSN: 0007-1250,1472-1465
DOI: 10.1192/bjp.163.4.556a