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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.
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The computer programs designed to mimic the role of the expert human consultant. This type of systems are capable to cope with the complex problems of the medical decision makin
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
2 jobs n machines,graphical method,how to determine which job should proceed first on each machine
The distribution over distributions in the sense that each draw from the process is itself the distribution. The name Dirichlet process or procedure is due to the fact that the ?ni
Component bar chart : A bar chart which shows the component parts of the aggregate represented by the whole length of the bar. The component parts are shown as the sectors of bar w
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
Common cause failures (CCF): Simultaneous failures of the number of components due to a same reason. A reason can be external to the components, or it can be the single failure wh
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
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