Big Data Analytics with Applications in Insider Threat Detection

13

Directions in Data Stream Classification

13.1 Introduction

We have discussed three major approaches for stream analytics in Chapters 10 through 12. In Chapter 10, we described our innovative technique for classifying concept-drifting data streams using a novel ensemble classifier originally discussed in [MASU09a]. It is a multiple partition, multiple chunk (MPC) ensemble classifier-based data mining technique to classify concept-drifting data streams. Existing ensemble techniques in classifying concept-drifting data streams follow a single-partition, single-chunk approach in which a single data chunk is used to train one classifier. In our approach, we train a collection of v classifiers from r consecutive data chunks using v-fold partitioning ...