M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 9, September 2015
Novel Class Detection for Feature Evolving Data Streams
Harshada Wagaskar, Prof. Gayatri Bhandari
Abstract: Data Stream Mining is the method of deriving knowledge from constant and quickly developing records of information. A data stream is an ordered sequence of occurrences. These occurrences can be read just once or a less number of times utilizing restricted using limited storage capabilities and computing. Examples of such data streams include ATM exchanges, sensor information, telephone discussions and so forth. Data stream characterization has many difficulties in the information mining field. The four major challenges in the field of Data stream classification which are infinite length, concept-drift and concept-evolution are proposed here. A data stream is never-ending in length, hence it is not practical to store and utilize all the historical data for training purpose. Concept-drift occurs as a result of changes in the fundamental concepts. Concept-evolution happens when new classes develop in the information data. An example of concept-evolution is Twitter, where new themes develop routinely in the stream of instant messages. Feature-evolution is a regularly happening process in data streams, where new features evolve and old features vanish. This problem is investigated during this paper, and improved solutions are proposed. The current work additionally addresses the recurring class problem in data streams.
Keywords: Data stream, concept-evolution, novel class, outlier
Edition: Volume 4 Issue 9, September 2015,
Pages: 1233 - 1237
How to Cite this Article?
Harshada Wagaskar, Prof. Gayatri Bhandari, "Novel Class Detection for Feature Evolving Data Streams", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=SUB158274, Volume 4 Issue 9, September 2015, 1233 - 1237
How to Share this Article?
Similar Articles with Keyword 'Data stream'
Lightning CEP - Joining on High Velocity Stream
Vikas Kale, Kishor Shedge
A Review on Detection of Outliers Over High Dimensional Streaming Data Using Cluster Based Hybrid Approach
Abhishek B. Mankar, Namrata Ghuse
Similar Articles with Keyword 'novel class'
Survey of Adaptive Novel Class Detection and Classification of Feature-Evolving Data Streams
Punam D. Dhande, Dr. A. M. Dixit
Survey on Categorization and Detection of Adaptive Novel Class of Feature Evolving Data Streams
Chaitrali T. Chavan, Prof. Vinod S. Wadne
Similar Articles with Keyword 'outlier'
Predicting Diabetes using Gradient Boosting is a Machine Learning Technique
Ali Adam Mohammad
A Survey on Outlier Detection Methods
Rajani S Kadam, Prakash R Devale
Similar Articles with Keyword 'Data'
Heart Disease Prediction with Machine Learning Approaches
A Study and Comparative Analysis of Cryptographic Algorithms for Various File Formats
M. Meena, A. Komathi
Similar Articles with Keyword 'stream'
An Opinion Mining for Indian Premier League Using Machine Learning Techniques
Rakshith N, Suraj B S, Chethana C
Music Recommendation System
Nipun Prakash Gupta, Durgesh Kumar