-1.0 -0.5 0.0 0.5 1.0 It is a classification data-set with the goal of separating the red and the black observations. Assume, that the number of red and black observations is approximately equal. Which of the following statements is correct? a) A Decision Tree can reach a prodiction error of (nearly) zero on this data-set. b) When performing a variable selection using the step-wise forward selection algorithm, neither of the variables I1, 12 will be added to the model. c) A Linear Discriminant Analysis (LDA) can reach a prediction error of (nearly) zero on this data-set. d) Every model using only one of the two variables 11, 1ą will have a misselassification error of approximately 50%. 00 0'1-

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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It is a classification data-set with the goal of separating the red and the black observations. Assume, that the
number of red and black observations is spproximately equal. Which of the following statements is correct?
a) A Decision Tree can reach a prediction error of (nearly) zero on this data-set.
b) When performing a variable selection using the step-wise forward selection algorithm, neither of the variables
I1, 12 will be added to the model.
c) A Linear Discriminant Analysis (LDA) can reach a prediction error of (nearly) zero on this data-set.
d) Every model using only one of the two variables 11, 12 will have a missclassification error of approximately
50%.
en-
01-
Transcribed Image Text:-1.0 -0.5 0.0 0.5 1.0 It is a classification data-set with the goal of separating the red and the black observations. Assume, that the number of red and black observations is spproximately equal. Which of the following statements is correct? a) A Decision Tree can reach a prediction error of (nearly) zero on this data-set. b) When performing a variable selection using the step-wise forward selection algorithm, neither of the variables I1, 12 will be added to the model. c) A Linear Discriminant Analysis (LDA) can reach a prediction error of (nearly) zero on this data-set. d) Every model using only one of the two variables 11, 12 will have a missclassification error of approximately 50%. en- 01-
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