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When is minimum mean square error algorithm used?
This type of algorithm is commonly used in n dimensional clustering applications. This mean is commonly the simplest to use and a typical algorithm employing the minimum square error algorithm can be found in McQueen 1967.
What types of data used in algorithm?
Whatever data you need. If you need the algorithm to operate with many different types of data, and you are programming in C++, you could use generic programming practices and use templates.
What is the difference between clustering and classification?
I've been looking for this aswer about a few months, and nothing! Researching on it, I believe that both are same. But, with only one markable difference: clustering is a type of unsupervised learning, and classification is a type of supervised learning. I believe that it is the only difference, and, of course, this dictates the way that the algorithm starts. But the results are essentially similar: grouped data.Good luck in your question. I hope I've helped!
What are the different types of routing algorithms?
1.robust 2.correct 3.optimal 4.error free 5.reliable
Difference between K-mean and K-medoids algorithm for clustering techniques in data mining?
Both of them utilize expectation-maximization strategy to converge to a minimum error condition. While K-Medoids require the cluster centters to be centroids, in k-Means the centers could be anywhere in the sample space. k-Medoids is more robust to outliners than k-Means therefore results in more quality clustering. It is also computationally more complex.
