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Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past experience. In essence this reduces to the study of computer algorithms improve automatically through experience. The computer program is said to learn from the past experience E with respect to some class of tasks T and performance gauge P, if its performance at tasks in T, as measured by P, gets improves with experience E. Machine learning is inherently a multidisciplinary field by making use of results and techniques from probability and statistics, information theory , computational complexity theory etc; it is closely related to the pattern recognition and artificial intelligence and is broadly used in modern data mining.
Basic reproduction number : A term used in the theory of infectious diseases for the number of secondary cases which one case would generate in a completely susceptible population.
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an oil company is considering whether or not to bid for an offshore drilling contract. The bid would cost $60 with a 65% chance of gaining the contract. Outcome success Probability
A term usually used for unobserved individual heterogeneity. Such variation is of main concern in the medical statistics particularly in the analysis of the survival times where ha
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if nR2 > MTB >
How do I report the results in the table?
Imprecise probabilities is a n approach used by soft techniques in which uncertainty is represented by the closed, convex sets of probability distributions and the probability of
It is the art of attempting to exchange something quite small and certain, for something which are large and uncertain. Gambling is big business; in the US, for instance, it is at
Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi
Barrett and Marshall Model for conception : A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sp
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