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3 Machine Learning Quiz Questions with Answers explanation, Interview
questions on machine learning, quiz questions for data scientist answers
explained, machine learning exam questions, question bank in machine
learning, classification, decision tree, two class classification, bayes net
Machine
learning MCQ - Set 22
1. Which of the
following classifiers can perfectly classify the following data?
a) Decision tree
b) Logistic
regression
c) Gaussian Naïve Bayes
d) All of the above
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Ans : (a)
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Answer: (a) Decision tree
Decision Tree
only.
Decision trees of
depth 2 which first splits on X and then on Y will perfectly classify it.
Logistic
regression leads to linear decision boundaries, hence cannot classify this
data perfectly.
Due to
conditional independence requirement, it is not possible to fit a Gaussian
that peaks at the labels of only one class and has no covariance between
features, so Gaussian Naive Bayes cannot classify this data perfectly.
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2. Which is the
correct joint distribution for the following Bayesian net?
a) P(A,B,C,D,E) =
P(E)P(C)P(D|E)P(A|C)P(B|D,E)
b) P(A,B,C,D,E) =
P(A)P(B)P(C|A)P(D|A,B,C)P(E|D)
c) P(A,B,C,D,E) =
P(A)P(B)P(C)P(D)P(E)P(E|A,B,C,D)
d) P(A,B,C,D,E) =
P(A)P(B)P(D|A,B,C)P(E|D)
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Ans : (b)
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Answer: (b) P(A,B,C,D,E) = P(A)P(B)P(C|A)P(D|A,B,C)P(E|D)
A Bayesian
network is a directed acyclic graph
in which each edge corresponds to a conditional dependency, and each node
corresponds to a unique random variable.
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3. For a two class
classification problem, which among the following are true?
a) In case both the
covariance matrices are spherical and equal, the within class variance term has
an effect on the LDA derived direction.
b) In case both the
covariance matrices are spherical and equal, the within class variance term has
no effect on the LDA derived direction.
c) In case both the
covariance matrices are spherical but unequal, the within class variance term
has an effect on the LDA derived direction.
d) In case both the
covariance matrices are spherical but unequal, the within class variance term
has no effect on the LDA derived direction.
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Ans : (b) and (d)
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Answer: (b) and (d)
It is easy to see
that if the covariance matrix for a particular class is spherical, then the ‘within
class variance’ is the same along all directions, and hence we can ignore
this component and focus solely on the ‘between class variance’ (i.e.,
identify the direction along which the between class variance is maximised).
Two class classification
A classification
problem with two classes is referred as two class classification or binary
classification problem. It is used to predict one of two possible outcomes.
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Related links:
Which classification algorithm can perfectly classify the given data
Define two class classification
What is the effect of 'within class variance' on LDA derived direction if both the covariance matrices are spherical
How to calculate the joint distribution of a bayes network
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