Optimization of Naïve Bayes Data Mining Classification Algorithm

Abstract

As a probability-based statistical classification method, the Naïve Bayesian classifier has gained wide popularity; however, the performance of Naive Bayes classification algorithm suffers in the domains (data set) that involve correlated features. [Correlated features are the features which have a mutual relationship or connection with each other. As correlated features are related to each other, they are measuring the same feature only, means they are redundant features]. This paper is focused upon optimization of Naive Bayes classification algorithms to improve the accuracy of generated classification results with reduced time to build the model from training dataset. The aim is to improve the performance of Naive Bayes algorithms by removing the redundant correlated features before giving the dataset to classifier. This paper highlights and discusses the mathematical derivation of Naive Bayes classifier and theoretically proves how the redundant correlated features reduce the accuracy of the classification algorithm. Finally, from the experimental reviews using WEKA data mining software, this paper presents the impressive results with significant improvement into the accuracy and time taken to build the model by Naive Bayes classification algorithm.

Authors and Affiliations

Maneesh Singhal, Ramashankar Sharma

Keywords

Related Articles

Study Steel Reinforced Concrete Beam Column Joints Performance under Exposure to Fire

Fire safety or fire resistance is a critical design consideration for high rise buildings since fire represents one of the most severe conditions that may be encountered during the life time of a building. Beam column j...

Quantum Realization Full Adder-Subtractor Circuit Design Using Islam gate

Quantum Computing is one of the emerging computing methods of future computing technologies. The construction of quantum computer that performs computation is implemented using Quantum Gate, the basic gate level element...

Automatic Buck-Boost Dc/Dc Converter for Automotive Application

dc/dc power converter is an electronic device that converts a source of direct current from one voltage level to another voltage level. It is a type of electric power converter. Power levels range from very low to very...

Design of Brushless DC Motor with Fuzzy Logic Controller

Actually brushless DC motor is the alternate motor for traditional motors and also comparatively brushless DC motor has improved performance in speed, torque, efficiency and electromagnetic torque. In this paper the thr...

A Booster and PWM Based Power Amplifier for Reaction Wheel

Reaction wheel is an inertial actuator in a spacecraft attitude control system and is used to generate suitable attitude control torques for correcting spacecraft attitude deviation or adjusting to an assigned attitude....

Download PDF file
  • EP ID EP18589
  • DOI -
  • Views 850
  • Downloads 25

How To Cite

Maneesh Singhal, Ramashankar Sharma (2014). Optimization of Naïve Bayes Data Mining Classification Algorithm. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(8), -. https://europub.co.uk/articles/-A-18589