Data stream mining is the process of extracting knowledge from continuous data. Data stream can be viewed as a sequence of relational touples arrives continuously at time varying. Classification of data stream is more challenging task due to three major problems in data stream mining: Infinite length, Concept-drift, Arrival of novel class. Novel class detection in stream data classification is interesting research topic and researches available for concept drift problem but not attention on the Novel class detection. In this paper we have discussed various techniques of the novel class detection. And have also covered comparative analysis of various techniques for the same.