The K-means algorithm:
A. requires the dimension of the feature space to be no bigger than the number of samples
B. has the smallest value of the objective function when k = 1
C. minimizes the within class variance for a given number of clusters
D. converges to the global optimum if and only if the initial means are chosen as some of the samples themselves
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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