Please I need the answers to the following question, it is true and false question, It is from data mining subject:

1-The distribution of data set which reflects a significant majority of the negative class and a minority of the positive class is called the underfitting problem. ( )

2-Pattern-Fusion merges small subpatterns of a large pattern instead of incrementallyexpanding patterns with single items. ( )

3- Constraints can be categorized into pattern-pruning and data-pruning constraints.( )

4-A colossal pattern has far more core patterns than a small-sized pattern. ( )

5- The root node in decision tree holds a class label.( )

6-Pattern-Fusion leads to the worst approximation of colossal patterns. ( )

7- In case of more than one classifier model for the same data, we may select the model with low error rate.( )

Thanks in advanced