How do you handle missing or corrupted data in a dataset?

What is the naive assumption in a Naive Bayes Classifier.

We usually use feature normalization before using the Gaussian kernel in SVM. What is true about feature normalization?
1. We do feature normalization so that new feature will dominate other
2. Some times, feature normalization is not feasible in case of categorical variables
3. Feature normalization always helps when we use Gaussian kernel in SVM

The minimum time complexity for training an SVM is O(n2). According to this fact, what sizes of datasets are not best suited for SVM's?

This clustering algorithm initially assumes that each data instance represents a single cluster.

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