Scheduled Theoretical Restoration for Mining Immensely Partial Data Sets
Journal Title: The International Journal of Technological Exploration and Learning - Year 2013, Vol 2, Issue 5
Abstract
Partial data sets have turn out to be just about ubiquitous in an extensive range of application fields. Mutual illustrations can be initiate in climate and image data sets, sensor data sets, and medical data sets. The partiality in these data sets may stand up from a number of issues: In some circumstances, it may merely be a replication of definite measurements not being obtainable at the time, in others, the data may be absent due to incomplete system failure, or it may merely be a consequence of users being reluctant to stipulate attributes due to confidentiality worries. When a important portion of the entries are lost in all of the attributes, it turn into very tough to perform any generous of sensible extrapolation on the unique data. For such circumstances, we present the innovative idea of theoretical restoration in which we make effective theoretical representations on which the data mining algorithms can be openly smeared. The desirability behind the idea of theoretical restoration is to practice the correlation structure of the data in directive to precise it in terms of ideas rather than the unique dimensions. As a outcome, the restoration procedure evaluates only those theoretical aspects of the data can be mined from the partial data set, rather than might faults formed by extrapolation. We reveal the efficiency of the method on a range of actual data sets.
Authors and Affiliations
K. A. VarunKumar| Department of Computer Science and Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, S. Sibi Chakkaravarthy| Department of Computer Science and Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, M. Prabakaran| Department of Electrical & Electronics Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, Ajay Kaurav| Department of Electrical & Electronics Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, R. Baskar| Department of Electrical & Electronics Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai, N. Nandhakishore| Department of Electrical & Electronics Engineering Vel Tech Dr.RR & Dr.SR Technical University, Chennai
Anomaly Based Intrusion Detection using Feature Relevance and Negative Selection Algorithm
With the increase in the use of internet, the job of malicious people has been made easy to exploit vulnerabilities in existing system. Intrusion Detection System (IDS) plays a major role in computer/network security...
Intelligent Battery Management System Analyzing & Optimizing of Multicell Battery Voltage
The battery management system (BMS) is a critical component of electric and hybrid electric vehicles. The purpose of the BMS is to guarantee safe and reliable battery operation. To maintain the safety and reliability...
Design and Implementation of Fast- Lifting Based Wavelet Transform for Image Compression
The digital data can be compressed and retrieved using Discrete Wavelet Transform (DWT) and Inverse Discrete wavelet Transform (IDWT). The medical images need to be compressed and retrieved without loosing of informa...
Design of Power Efficient and High Speed Carry Select Look Ahead Adder Using SP-D3l Logic
Minimizing area and power is the most challenging task in modern VLSI design. Adders are the most extensively used components in many integrated circuits; the design of power efficient high-speed data path logic syste...
Emotional Maturity: Characteristics and Levels
"Mature" means a completed natural growth. Emotional maturity is not related to physical maturity which is expected to be but, does not grow with our chronological age. Emotionally mature people are sensible who do no...