Machine learning, Advanced Statistics

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. 

Posted Date: 7/30/2012 2:53:54 AM | Location : United States







Related Discussions:- Machine learning, Assignment Help, Ask Question on Machine learning, Get Answer, Expert's Help, Machine learning Discussions

Write discussion on Machine learning
Your posts are moderated
Related Questions
The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan

Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators

Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.

This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o

Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of succes


Jelinski  Moranda model is t he model of software reliability which supposes that failures occur according to the Poisson process with a rate decreasing as more faults are diagnos

Interior analysis is the  term now and again applied to analysis carried out on the fitted model in regression problem. The basic target of such analyses is the identification of

Randomized response technique : The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what quer

Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th