Different methods of clustering and compare the results

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Mark the following statements as being True or False. If False, correct the statement to be true.

(a) The main difficulty with assessing missing data is to determine why it is missing, whether it is due to omission, inability to find or enter a value, or if a null value represents something tangible.

(b) Hierarchical clustering methods require a predefined number of cluster, similar to k-means clustering.

(c) One way to assess reliability and validity of clustering is to use different methods of clustering and compare the results.

(d) Cluster analysis is a technique for analyzing data when the criterion or dependent variable is categorical, and the independent variables are interval in nature

(e) Discriminant functions are linear combinations of the predictor or independent variables, which will best discriminate between categories of the criterion or dependent variable groups.

Reference no: EM131963956

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