A Comparative Study on University Admission Predictions Using Machine Learning Techniques
نویسندگان
چکیده
منابع مشابه
Machine Learning Classification Techniques: A Comparative Study
Machine learning is the study of computer algorithms that improve automatically with experience. In other words it is the ability of the computer program to acquire or develop new knowledge or skills from examples for optimising the performance of a computer or a mobile device. In this paper we apply machine learning techniques Bayes network, Logistic Regression, Decision Stump, J48, Random For...
متن کاملAccurate contact predictions using covariation techniques and machine learning
Here we present the results of residue-residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effective sequences, our server achieved an average top-L/5 long-range contact precision of 27%. MetaPSICOV method bases on a combination of classical cont...
متن کاملMachine-Learning Techniques for Customer Retention: A Comparative Study
Nowadays, customers have become more interested in the quality of service (QoS) that organizations can provide them. Services provided by different vendors are not highly distinguished which increases competition between organizations to maintain and increase their QoS. Customer Relationship Management systems are used to enable organizations to acquire new customers, establish a continuous rel...
متن کاملBankruptcy Prediction by Supervised Machine Learning Techniques : A Comparative Study
It is very important for financial institutions which are capable of accurately predicting business failure. In literature, numbers of bankruptcy prediction models have been developed based on statistical and machine learning techniques. In particular, many machine learning techniques, such as neural networks, decision trees, etc. have shown better prediction performances than statistical ones....
متن کاملA Comparative Study of Malware Detection Techniques Using Machine Learning Methods
In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to mi...
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 Scientific Research in Computer Science, Engineering and Information Technology
سال: 2021
ISSN: 2456-3307
DOI: 10.32628/cseit2172107