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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.
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
Kurtosis: The extent to which the peak of the unimodal probability distribution or the frequency distribution departs from its shape of the normal distribution, by either being mo
Genstat: The basic purpose piece of statistical software for the management and the analysis of data. The package incorporates the wide variety of data handling events and a wi
Population pyramid : The diagram designed to show the comparison of the human population by sex and age at a given instant time, consisting of a pair of the histograms, one for eve
I have a problem I am trying to solve. An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is
elements , importance, limitation, and theories
The special cases of the probability distributions in which the random variable's distribution is concentrated at one point only. For instance, a discrete uniform distribution when
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
Average age at death : A ?awed statistic summarizing expectancy of the life and other aspects of the mortality. For instance, a study comparing average age at the death for male sy
methods of determining trend in time series?
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