E20-007 試験問題を無料オンラインアクセス

Refer to the exhibit.

You have run a linear regression model against your data, and have plotted true outcome versus predicted outcome. The R-squared of your model is 0.75. What is your assessment of the model?

• A.The R-squared may be biased upwards by the extreme-valued outcomes. Remove them and refit to get a better idea of the model's quality over typical data.
• B.The observations seem to come from two different populations,but this model fits them both equally well.
• C.The R-squared is good. The model should perform well.
• D.The extreme-valued outliers may negatively affect the model's performance. Remove them to see if the R-squared improves over typical data.

Refer to the exhibit.

In the exhibit, the x-axis represents the derived probability of a borrower defaulting on a loan. Also in the exhibit, the pink represents borrowers that are known to have not defaulted on their loan, and the blue represents borrowers that are known to have defaulted on their loan.
Which analytical method could produce the probabilities needed to build this exhibit?

• A.Discriminant Analysis
• B.Linear Regression
• C.Logistic Regression
• D.Association Rules

You are attempting to find the Euclidean distance between two centroids:
Centroid A's coordinates: (X = 2, Y = 4)
Centroid B's coordinates (X = 8, Y = 10)
Which formula finds the correct Euclidean distance?

• A.SQRT(((2-8) x 2) + ((4-10) x 2)) or 12.17
• B.SQRT((2-8)2+(4-10)2) or 8.49
• C.((2-8)2+(4-10)2) or 72
• D.((2-8) x 2 + (4-10) x 2) or 148

Refer to the exhibit Consider the training data set shown in the exhibit. What are the classification (Y = 0 or 1) and the probability of the classification for the tuple

X(1, 0, 0)
using Naive Bayesian classifier?

• A.Classification Y = 0,Probability = 4/54
• B.Classification Y = 1,Probability = 1/54
• C.Classification Y = 0,Probability = 1/54
• D.Classification Y = 1,Probability = 4/54

You are studying the behavior of a population, and you are provided with multidimensional data at the individual level. You have identified four specific individuals who are valuable to your study, and would like to find all users who are most similar to each individual. Which algorithm is the most appropriate for this study?

• A.Decision trees
• B.Association rules
• C.K-means clustering
• D.Linear regression