Question

Noisy values are the values that are valid for the dataset, but are incorrectly recorded. Is it?

Answer 1

True. Noisy values are the values that are valid for the dataset, but are incorrectly recorded.

Explanation :

• In Data mining, Noisy values is the incorrect and inconsistent data inserted into the data sets.

• They are valid and needed. The noisy data can be any thing. For example, if in a set, ages of the students in a class is recorded and one value among them is recorded incorrectly as 199, that value will be considered as noisy. It is valid, but incorrectly recorded.

• These type of errors can be handled using various ways, such as filling such places with a mean value of correct elements of set, or by placing a common variable like "FALSE" or "NaN" etc,  that tells us that it is an incorrect value. If the incorrect values or more in number, we can simply ignore that set.

• So, we can finalize that the statement "Noisy values are the values that are valid for the dataset, but are incorrectly recorded" is TRUE.

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