We have been given a dataset with n records in which we have input attribute as x and output attribute as y. Suppose we use a linear regression method to model this data. To test our linear regressor, we split the data in training set and test set randomly. Now we increase the training set size gradually. As the training set size increases, what do you expect will happen with the mean training error?
A. increase
B. decrease
C. remain constant
D. can't say
Answer: Option D
This Question Belongs to Computer Science >> Machine Learning
Related Questions on 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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