Earticle

초록

영어

Predictive modeling is the process of creating a statistical model from data with the purpose of predicting future behavior. In recent years, the amount of available data has increased exponentially and “Big Data Analysis” is expected to be at the core of most future innovations. Due to the rapid development in the field of data analysis, there is still a lack of consensus on how one should approach predictive modeling problems in general. Another innovation in the field of predictive modeling is the use of data analysis competitions for model selection. This competitive approach is interesting and seems fruitful, but one could ask if the framework provided by for example Gane Project based on big data framework gives a trustworthy resemblance of real-world predictive modeling problems. In this thesis, we will state and test a set of hypotheses about predicative modeling, both in general and in the scope of data analysis competitions. We will then describe a conceptual big data framework for approaching predictive modeling problems. To test the validity and usefulness of this framework, we will participate in a series of predictive modeling competitions on the platform provided by Gane, and describe our approach to these competitions.

목차

Abstract
 1. Introduction
 2. Conceptual Modeling
 3. Big Data
  3.1. Gane Data
 4. A Framework for Predictive Modeling
  4.1. Exploratory Analysis of Gane data
  4.2. Feature Engineering
 5. Algorithmic Evaluation
 6. Related Works
  6.1. Complexity
  6.2. Completeness
  6.3. Usability
 7. Conclusions
 References

키워드

저자

• Jeong-Sig Kim [ Department of Computer and Mobile Convergence, Gyeonggi College of Science and Technology, 269, Gyeonggigwagi-dearo, Siheung-si, Gyeonggi-do, Korea ]
• Eung-Sung Kim [ Department of Computer and Mobile Convergence, Gyeonggi College of Science and Technology, 269, Gyeonggigwagi-dearo, Siheung-si, Gyeonggi-do, Korea ]
• Jin-Hong Kim [ College of Information and Communication Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605