Machine Learning Questions

Question 1.
The result of a confusion matrix is as below:
Confusion Matrix Actual value
faulty(0) Good(1)
Prediction faulty(0) 50 3
Good(1) 5 42
What is the accuracy value?
Group of answer choices

92%

8%

50%

42%

Question 2.
A researcher has conducted a research to evaluate the relationship between age and the height of the students in a class. His results revealed the correlation of -1.0 between age and height. What is the conclusion of this research?
Group of answer choices

There is a strong negative relationship between age and height

There is a strong positive relationship between age and height

There is no relationship between age and height

There is a weak relationship between age and height

Question 3.
Which of the following statements is correct?
Group of answer choices

Multivariable and Multivariate regression are the same thing, i.e. each involve multiple features (independent variables) and one response (dependent variable).

There is no way to make a 2-way split on continuous data.

If we complete an analysis and find that there is statistically significant evidence of a relationship between a predictor variable and its corresponding response variable we can safely assert that we know the predictor caused the response.

Decision tree induction algorithms use what is called a greedy strategy but then may only find a local minimum.

Question 4:
Remember the dataset of alligators in Lecture 3 which was about the length and weight of several aligators in Florida. . The variable X is the length of aligator and the Y variable is the weight of them. A researcher decided to use decision tree and designed two steps: X4 . What is the name of this method of splitting?
Group of answer choices

Entropy classification

Gini index

Binary splitting

Multi-way splitting

Question 5:
Which one is NOT one of the disadvantages of decision tree?
Group of answer choices

In a complex model, it may result to an overfitting

Small variations in features may affect the trees

It is not useful when we have targets with more than 2 levels

If some of the target variables overcome the others, it may result in biased trees

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