Which among the following statements best describes our approach to learning decision trees
A. identify the best partition of the input space and response per partition to minimise sum of squares error
B. identify the best approximation of the above by the greedy approach (to identifying the partitions)
C. identify the model which gives the best performance using the greedy approximation (option (b)) with the smallest partition scheme
D. identify the model which gives performance close to the best greedy approximation performance (option (b)) with the smallest partition scheme
Answer: Option B
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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