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Exam Code:
DS-200Exam Name: Data Science Essentials Beta
One year free update, No help, Full refund!
DS-200 Exam Tests Total Q&A: 60 Questions and Answers
Last Update: 04-23,2015
DS-200 Exam PDF Detail : Click Here
NO.1 Under what two conditions does stochastic gradient descent outperform
2nd-order
optimization techniques such as iteratively reweighted least
squares?
A. When the volume of input data is so large and diverse that a
2nd-order optimization technique
can be fit to a sample of the data
B.
When the model's estimates must be updated in real-time in order to account
for
newobservations.
C. When the input data can easily fit into memory on
a single machine, but we want to calculate
confidence intervals for all of
the parameters in the model.
D. When we are required to find the parameters
that return the optimal value of the objective
function.
Answer:
A,B
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NO.2 Why should stop an interactive machine learning
algorithm as soon as the performance of the
model on a test set stops
improving?
A. To avoid the need for cross-validating the model
B. To
prevent overfitting
C. To increase the VC (VAPNIK-Chervonenkis) dimension for
the model
D. To keep the number of terms in the model as possible
E. To
maintain the highest VC (Vapnik-Chervonenkis) dimension for the model
Answer:
B
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NO.3 What is the most common reason for a k-means
clustering algorithm to returns a sub-optimal
clustering of its input?
A.
Non-negative values for the distance function
B. Input data set is too
large
C. Non-normal distribution of the input data
D. Poor selection of
the initial controls
Answer: C
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NO.4 Refer to the
exhibit.
Which point in the figure is the mean?
A. A
B. B
C.
C
Answer: B
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NO.5 What is
default delimiter for Hive tables?
A.