Question

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

Answer 1

Noisy data that are not properly recorded by the machine are valid for the dataset.  

Explanation:

The noisy data cannot be interrupted. The noisy data results in increase of storage space thereby affecting the process of data mining adversely. There can be multiple causes of the noisy data including hardware failures or programming errors. Sometimes, removing the original data that has to be received is also termed as noisy data.

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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