Student Performance Prediction using Machine Learning
نویسندگان
چکیده
منابع مشابه
Prediction of Student Learning Styles using Data Mining Techniques
This paper focuses on the prediction of student learning styles using data mining techniques within their institutions. This prediction was aimed at finding out how different learning styles are achieved within learning environments which are specifically influenced by already existing factors. These learning styles, have been affected by different factors that are mainly engraved and found wit...
متن کاملStock Price Prediction using Machine Learning and Swarm Intelligence
Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...
متن کاملUsing Machine Learning Techniques for Performance Prediction on Multi-Cores
Sharing of resources by the cores of multi-core processors brings performance issues for the system. Majority of the shared resources belong to memory hierarchy sub-system of the processors such as last level caches, prefetchers and memory buses. Programs co-running on the cores of a multi-core processor may interfere with each other due to usage of such shared resources. Such interference caus...
متن کاملEarly Prediction of Students Performance using Machine Learning Techniques
In recent years Educational Data Mining (EDM) has emerged as a new field of research due to the development of several statistical approaches to explore data in educational context. One such application of EDM is early prediction of student results. This is necessary in higher education for identifying the "weak" students so that some form of remediation may be organized for them. In ...
متن کاملStudent Speech Act Classification Using Machine Learning
Dialogue-based intelligent tutoring systems use speech act classifiers to categorize student input into answers, questions, and other speech acts. Previous work has primarily focused on question classification. In this paper, we present a complimentary speech act classifier that focuses primarily on non-questions, which was developed using machine learning techniques. Our results show that an e...
متن کاملذخیره 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 Computer Science and Mobile Computing
سال: 2020
ISSN: 2320-088X
DOI: 10.47760/ijcsmc.2020.v09i09.004