In a linear regression problem, we are using "R-squared" to measure goodness-of-fit. We add a feature in linear regression model and retrain the same model. Which of the following option is true?
A. If R Squared increases, this variable is significant.
B. If R Squared decreases, this variable is not significant.
C. Individually R squared cannot tell about variable importance. We can't say anything about it right now.
D. None of these.
Answer: Option C
This Question Belongs to Computer Science >> Machine Learning
In simple term, machine learning is
A. training based on historical data
B. prediction to answer a query
C. both A and B
D. automization of complex tasks
Which of the following is the best machine learning method?
A. scalable
B. accuracy
C. fast
D. all of the above
The output of training process in machine learning is
A. machine learning model
B. machine learning algorithm
C. null
D. accuracy
Application of machine learning methods to large databases is called
A. data mining.
B. artificial intelligence
C. big data computing
D. internet of things
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