Sequential pattern mining involves identifying statistically significant patterns in sequential data, which refers to ordered data points. The document also discusses the distinction between classification and clustering in data mining. Additionally, it addresses the calculation of mean values in clusters derived from binary transaction datasets and their interpretations.

1. 1) Sequential pattern mining is a topic of data mining concerned
with finding statistically relevant patterns between data
examples where the values are delivered in a sequence. Discuss
what is sequential data? What is sequential pattern mining?
Explain difference between classification and clustering in data
mining.
2) Consider the mean of a cluster of objects from a binary
transaction data set. What are the minimum and maximum
values of the components of the mean? What is the
interpretation of components of the cluster mean? Which
components most accurately characterize the objects in the
cluster?