Beware of the man of one method or one instrument, either experimental or theoretical. He tends to become method oriented rather than problem oriented. The method-oriented man is shackled: the problem-oriented man is at least reaching freely toward what is most important. 52 Context Machine Learning is a sub-discipline of Information and Communication Technology (ICT) that develops the technologies for machines to recognise and learn patterns in data. It is distinct from, although related to, statistics. It can be differentiated by its focus on creating technology rather than the human-centred analysis of data. It is the science and engineering behind Data Mining. Machine learning is pervasive: it plays a key role in all stages of the scientific process and across diverse fields including bioinformatics, engineering and finance. It is widely accepted that ICT plays an enabling role across almost all technological disciplines. Analogously, Machine Learning plays an enabling role across most parts of ICT, from embedded to enterprise systems, and consequently is a crucial enabler of the Digital Economy 16. Vast quantities of data are now routinely collected and stored because it is affordable to do so. Machine learning makes sense of this data flood. The Problem The massive reduction in the cost of collecting, storing, transporting and processing

Testing canonical parameters in exponential models:

Abstract not found

Testing canonical parameters in exponential models:

genome-scale screening