Question

Explain what is meant by the terms below as a limitation of Pattern Discovery. Provide an example for them.

-poor data quality

-opportunity

-intervention

-separability

-oblivious

-non-stationarity

Answer 1

here I am going to describe about what is meant by the poor data quality, opportunity, intervention, separability, obvious and non stationary as limitation of pattern discovery along with the examples.

1) POOR DATA QUALITY :- when the data quality is poor it tends to release the poor quality models or projects. the poor data quality can be termed as the incomplete or missing data or missing values that can affect the the desired results.

2) OPPORTUNITY :- opportunity is that term which can convert the possibilities into desired actions. Video album opportunities we can convert our desire or possibilities into real actions.

3) INTERVENTION :- intervention is the misconduct in between the work that damage the real data action or distort the real data action. Intervention is the interruption between the data by someone else.

4) SEPARABILITY :- separability of the information or the data can be a hindrance when it comes to the pattern discovery can be really dangerous as a data can be damaged or distort. Damage of data can be obstacle in the success of the pattern discovery.

5) OBLIVIOUS :- important discovery when the data is unchangeable and oblivious it can be rigid and can be difficult to deal with. When the data is four digit changes cannot be made and we have to tackle with the same data no matter what.

6) NON STATIONARY :- when the data of the information is non stationary it can be a problematic situation when it comes to the pattern discovery as the non sectional data is of no particular use. and stationary daughter is lot more of use than that of the non stationary data.

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