Top 5 Machine Learning Quiz Questions with Answers explanation, Interview
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Machine
learning MCQ - Set 18
1. Which of the following would
indicate that a dataset is not bell shaped?
(a) The range is equal to
5 standard deviations.
(b) The range is larger
than the interquartile range.
(c) The mean is much
smaller than the median.
(d) There are no outliers.
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Ans : (c)
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Answer: (c) The mean is
much smaller than the median
If the mean is
much smaller than the median (mean < median), the curve will be skewed to
the left. Due to this, we cannot get a bell shaped curve.
Bell shaped curve
(normal distribution)
Bell shaped curve
depicts the normal distribution. The bell curve is perfectly symmetrical. It
is concentrated around the peak and decreases on either side. In a bell
curve, the peak represents the most probable event in the dataset while the
other events are equally distributed around the peak. The peak of the curve
corresponds to the mean of the dataset. In a normal probability distribution
also equals the median and the mode.
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2. Which statement is not true about
confidence intervals?
(a) A confidence interval
is an interval of values computed from sample data that is likely to include the
true population value.
(b) An approximate formula
for a 95% confidence interval is sample estimate ± margin of error.
(c) A confidence interval
between 20% and 40% means that the population proportion lies between 20% and
40%.
(d) A 99% confidence
interval procedure has a higher probability of producing intervals that will include
the population parameter than a 95% confidence interval procedure.
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Ans : (c)
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Answer: (c) A confidence
interval between 20% and 40% means that the population proportion lies
between 20% and 40%.
All the other
options are true about the confidence interval except option (c).
Confidence
intervals are a way of quantifying the uncertainty of an estimate. It is a
range of values we are fairly sure our true value lies in.
In the confidence
interval calculation, the value comes after the symbol ± is the margin of error which can be calculated using Z
score, standard deviation and the square root of sample size. Confidence
interval can be calculated using the following equation;
X̄ ±
Z * ( s / √n)
99% confidence
interval will include a larger margin of error hence having the higher
probability of producing intervals.
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3. Which of the following denotes the
expected value of a random variable?
(a) It is a value that has
the highest probability of occurring.
(b) It is the mean value
over an infinite number of observations of the variable.
(c) It is the largest
value that will ever occur.
(d) It is most common
value over a finite number of observations of the variable.
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Ans : (b)
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Answer: (b) It is the
mean value over an infinite number of observations of the variable.
The expected value
is also called the mean or average of a discrete random variable X. It is a
weighted average of the possible values that X can take, each value being
weighted according to the probability of that event occurring. The expected
value of X is usually written as E(X).
The expected
value measures the center of the probability distribution - center of mass.
If all the values
are equally probable then the expected value is just the usual average of the
values. Expected value is also referred as mathematical expectation.
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4. Which of the following is INCORRECT
about the requirements of any distance metric?
(a) The distance must
never be negative
(b) The distance between
two identical vectors, x and y, is a non-zero value.
(c) The distance from x to
y is the same as the distance from y to x
(d) The metric must
satisfy the triangular inequality
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Ans : (b)
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Answer: (b) The distance
between two identical vectors, x and y, is a non-zero value
The distance
between two identical vectors, x and y, is zero. If two vectors have the same magnitude and the same direction, they are said to be equal (identical).
The angle between equal vectors is equal to zero degrees
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5. Which of the following distance
measures calculates the distance between two binary vectors?
(a) Euclidean distance
(b) Manhattan distance
(c) Minkowski distance
(d) Hamming
distance
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Ans : (d)
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Answer: (d) Hamming
distance
Hamming distance
calculates the distance between two binary vectors, also referred to as
binary strings or bitstrings for short. the Hamming distance between two
strings of equal length is the number of positions at which the corresponding
symbols are different. In other words, it measures the minimum number of
substitutions required to change one string into the other, or the minimum
number of errors that could have transformed one string into the other.
[Wikipedia]
Eulidean,
Manhattan, and Minkowski distance metrics measures the distance between two
real-valued vectors.
A distance
function provides distance between the elements of a set. If the distance is
zero then elements are equivalent else they are different from each other.
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What is margin of error in confidence interval calculation
What is the distance between two identical vectors? It is zero
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