Hyper Parameter Optimization using Genetic Algorithm on Machine Learning Methods for Online News Popularity Prediction
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 12
Abstract
Online news is a media for people to get new information. There are a lot of online news media out there and a many people will only read news that is interesting for them. This kind of news tends to be popular and will bring profit to the media owner. That’s why, it is necessary to predict whether a news is popular or not by using the prediction methods. Machine learning is one of the popular prediction methods we can use. In order to make a higher accuracy of prediction, the best hyper parameter of machine learning methods need to be determined. Determining the hyper parameter can be time consuming if we use grid search method because grid search is a method which tries all possible combination of hyper parameter. This is a problem because we need a quicker time to make a prediction of online news popularity. Hence, genetic algorithm is proposed as the alternative solution because genetic algorithm can get optimal hypermeter with reasonable time. The result of implementation shows that genetic algorithm can get the hyper parameter with almost the same result with grid search with faster computational time. The reduction in computational time is as follows: Support Vector Machine is 425.06%, Random forest is 17%, Adaptive Boosting is 651.06%, and lastly K - Nearest Neighbour is 396.72%.
Authors and Affiliations
Ananto Setyo Wicaksono, Ahmad Afif Supianto
Keywords
Related Articles
- EP ID EP429179
- DOI 10.14569/IJACSA.2018.091238
- Views 106
- Downloads 0
FPGA based Hardware-in-the-Loop Simulation for Digital Control of Power Converters using VHDL-AMS
This paper presents a new approach for complex system design, allowing rapid, efficient and low-cost prototyping. Using this approach can simplify designing tasks and go faster from system modeling to effective hardware...
Investigating Clinical Decision Support Systems Success Factors with Usability Testing
Clinical Decision Support Systems (CDSS) have been used widely since 2000s to improve the healthcare quality. CDSS can be utilized to support healthcare services as a tool to diagnose, predict, as well as to provide clin...
Metrics for Event Driven Software
The evaluation of Graphical User Interface has significant role to improve its quality. Very few metrics exists for the evaluation of Graphical User Interface. The purpose of metrics is to obtain better measurements in t...
Optimal Network Design for Consensus Formation: Wisdom of Networked Agents
The wisdom of crowds refers to the phenomenon in which the collective knowledge of a community is greater than the knowledge of any individual. This paper proposes a network design for the fastest and slowest consensus f...
Review of Energy Reduction Techniques for Green Cloud Computing
The growth of cloud computing has led to uneconomical energy consumption in data processing, storage, and communications. This is unfriendly to the environment, because of the carbon emissions. Therefore, green IT is req...