Misclassifying an actual ______ observation as a(n) ______ ...

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Misclassifying an actual ______ observation as a(n) ______ observation is known as a false positive.
 a. Class 0, Class 1
  b. Class 1, Class 0
  c. error, accuracy
  d. false, true

Question 2

A method for modifying variables that reduces bias prior to cluster analysis is
 a. standardization.
 
  b. weighting.
 
  c. removing outliers.
  d. randomizing.

[Heffejeff]

Answer to Question 1

a
RATIONALE: Misclassifying an actual Class 1observation as a Class 0 observation is known as a false positive.

Answer to Question 2

a
RATIONALE: The conversion to z-scores makes it easier to identify outlier measurements, which can distort the Euclidean distance between observations. Standardizing (or normalizing) observations removes bias due to the difference in measurement units, and variable weighting allows the analyst to introduce appropriate bias based on the business context.

[pane00]

TYSM

[JCABRERA33]

Great answer, keep it coming