If the Data Changes i.e. new data comes what happens to k-nearest neighbor and k-means clustering?

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If the Data Changes i.e. new data comes what happens to k-nearest neighbor and k-means clustering?

How is the computational complexity of k-nearest neighbor and k-means clustering? Are they do once and use always solution?

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How is the computational complexity of k-nearest neighbor and k-means clustering? Are they do once and use always solution?

Are k-nearest neighbor and k-means clustering both supervised and/or unsupervised?

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Are k-nearest neighbor and k-means clustering both supervised and/or unsupervised?

What are the differences between k-nearest neighbor and k-means clustering?

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What are the differences between k-nearest neighbor and k-means clustering?

What is Regression? When do we use Regression? Is Regression a Learning? i.e. a Machine Learning?

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What is Regression? When do we use Regression? Is Regression a Learning? i.e. a Machine Learning?

What is the assumption of the Input in Naive Bayes?

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What is the assumption of the Input in Naive Bayes?

Does Naive Bayes uses Conditional Probability? If so how and why?

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Does Naive Bayes uses Conditonal Probability? If so how and why?

What is Naive Bayes? Why is it called Naive Bayes?

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What is Naive Bayes? Why is it called Naive Bayes?

What is Stacking?

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What is Stacking?

What is Bagging?

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What is Bagging?