Big Data Analytics with Applications in Insider Threat Detection

10

A Multi-Partition, Multi-Chunk Ensemble for Classifying Concept-Drifting Data Streams

10.1 Introduction

While the challenges and prior work for stream data classification were discussed in Chapters 8 and 9, in this chapter, we describe our innovative technique for classifying concept-drifting data streams using a novel ensemble classifier originally discussed in [MASU09]. It is a multiple partition of 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 (SPC) approach, in which a single data chunk is used to train one classifier. In our approach, we train a collection ...