Question

Noisy values are the values that are valid for the dataset, but are incorrectly recorded?true or false

Answer 1

‘Noisy values are the values that are valid for the dataset, but are incorrectly recorded?’ is a TRUE statement.

Explanation:

• The noisy data can also be referred as a meaningless data or a corrupted data. In wave theory, the noise signals are considered as invalid meaningless signals.  

• Similarly, in data mining, noisy value can be considered as any data which neither be interpreted nor understand correctly.  

• The problem raised due to noisy values is outliers. This means the data object along with its characteristics are differed from other data objects.

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Answer 2

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 anything. For example, if in a set, the ages of the students in a class are 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 the 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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