A Hybrid Approach to Improve Classification Performance using WMOT Tool

Web usage mining is very important now a days due to huge amount of data processed day by day and it increase very rapidly on daily basis. Web usage mining is to utilize data mining techniques meant for web log data in order to recognize and extract the information of people using those websites. Authors presented a tool and analysed the web log data and classified it further with classification algorithms like Random Forest and use their own tool WMOT tool that's implemented new algorithms embedded with Random Forest algorithm like RFGA (Random Forest with genetic algorithm), RFACO (Random Forest with ant colony optimization) and use hybrid approach of genetic algorithm with ant colony feature selection in RFGAACO. In this paper authors summarized the experimental results of RF, RFGA, RFACO and RFGAACO and calculate their efficiency level over the web server log data and analysed the results.