Predicting Study Programme Selection with Data Mining Classification Technique

نویسندگان

چکیده

The application of data mining in the field education (Educational Data Mining - EDM) is becoming more and popular. Predicting final grades during studies, measuring student lecturer performance, targeting students, curriculum improvement, are just some examples that can support development this area. focus article on prediction study programme students will select their higher at Faculty Business Economics Bijeljina. analysis was conducted faculty wherein first two years attend same courses, while beginning third year they a specific programme. aim paper to use classification methods predict selected based achieved courses study. highest accuracy obtained using random forest algorithm (59,94%). Model evaluation results show choice does not depend only success all performed open-source WEKA tool, were presented interpreted.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Negative Selection Based Data Classification with Flexible Boundaries

One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...

متن کامل

Predicting the Next State of Traffic by Data Mining Classification Techniques

Traffic prediction systems can play an essential role in intelligent transportation systems (ITS). Prediction and patterns comprehensibility of traffic characteristic parameters such as average speed, flow, and travel time could be beneficiary both in advanced traveler information systems (ATIS) and in ITS traffic control systems. However, due to their complex nonlinear patterns, these systems ...

متن کامل

the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance

با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...

Predicting Type2 Diabetes Using Data Mining Algorithms

Background and purpose: Today, information systems and databases are widely used and in order to achieve higher accuracy and speed in making diagnosis, preventing the diseases, and choosing treatments they should be merged with traditional methods. This study aimed at presenting an accurate system for diagnosis of diabetes using data mining and a heuristic method combining neural network and pa...

متن کامل

Dynamic Algorithm Selection for Data Mining Classification

Recommending appropriate classification algorithm for given new dataset is very important and useful task but also is full of challenges. According to NO-FREE-LUNCH theorem, there is no best classifier for different classification problems. It is difficult to predict which learning algorithm will work best for what type of data and domain. In this paper, a method of recommending classification ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International journal of electrical engineering and computing

سال: 2022

ISSN: ['2566-3682']

DOI: https://doi.org/10.7251/ijeec2102094b