FUNDAMENTALS OF COMPUTER

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DATABASE FUNDAMENTALS

BASICS OF BIG DATA

Question [CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
True or False?Statement 1:Maximum likelihood estimation is a method that determines values for the parameters of a model. The parameter values are found such that they maximize the likelihood that the process described by the model produced the data that were actually observed.Statement 2:Bagging provides an averaging over a set of possible datasets, removing noisy and non-stable parts of models.
A
Only statement 1 is true
B
Only statement 2 is true
C
Both statements are true
D
Both statements are false
Explanation: 

Detailed explanation-1: -Maximum Likelihood Estimation is a probabilistic framework for solving the problem of density estimation. It involves maximizing a likelihood function in order to find the probability distribution and parameters that best explain the observed data.

Detailed explanation-2: -Maximum likelihood provides a consistent approach to parameter estimation problems. This means that maximum likelihood estimates can be developed for a large variety of estimation situations. For example, they can be applied in reliability analysis to censored data under various censoring models.

Detailed explanation-3: -Maximum likelihood estimation is a method that determines values for the parameters of a model. The parameter values are found such that they maximise the likelihood that the process described by the model produced the data that were actually observed.

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