Question

In deviation detection, new data is compared with a set of data called ____ data. Before data mining, it is important to remove ___ data from databases. 1st blank- cleansing, training, reporting 2nd blank- training, test, noisy

Answer 1

In deviation detection, new data is compared with a set of data called training data. Before data mining, it is important to remove noisy data from databases.

Step-by-step explanation:

In deviation detection, new data is compared with a set of data called training data. Before data mining, it is important to remove noisy data from databases.

Deviation detection is a technique used in data mining to identify outliers or abnormal data points. The training data consists of a set of normal or expected data points. New data is compared with this training data to identify any deviations or anomalies.

Noisy data refers to data that contains errors or inconsistencies. Before performing data mining, it is important to clean the databases by removing noisy data to ensure accurate and reliable results.