This data transformation technique works well when minimum and maximum values for a real-valued attribute are known.
A) min-max normalization
B) decimal scaling
C) z-score normalization
D) logarithmic normalization

Question

Quizplus · Accepted Answer

Min-max normalization is the best choice in this scenario as it scales the values of the attribute between 0 and 1 based on their minimum and maximum values. This helps in avoiding biases and makes the values easier to interpret and compare. Decimal scaling can also be used, but it is not as effective as min-max normalization. Z-score normalization and logarithmic normalization are not suitable for this scenario as they are used for transforming attributes with normal or skewed distributions, respectively.

This Data Transformation Technique Works Well When Minimum and Maximum