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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.
Bivariate survival data : The data in which the two related survival times are of interest. For instance, in familial studies of disease incidence, data might be available on the a
For a career woman, wearing lipstick has become an integral part of her daily life. It is not unusual for a woman to look for a lipstick that will stay on her lips and not smudge
Matching coefficient is a similarity coefficient for data consisting of the number of binary variables which is often used in cluster analysis. It can be given as follows he
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0 i =0, 1, 2, 3
Hurdle Model: The model for count data which postulates two processes, one generating the zeros in the data and one generating positive values. The binomial model decides the bina
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
properties of chebyshevs lemma
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
calculate absorbance value from concentration
This term sometimes used to describe the extra factor in variance of the sample mean when n sample values are drawn without the replacement from the finite population of size N. Th
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