Machine learning and data mining methods can be the future of the clinical decision process like pathological diagnosis. In this project we studied Breast Cancer Wisconsin dataset and applied different algorithms, concretely classifiers, in order to predict th…
Organizations and individuals nowadays are more and more willing to outsource their data to save storage and management costs, especially with the push for cloud computing which is service-oriented and offers both storage and computation scalability. However,…
Data analytics and Big Data application research, along with new structures in complex data, are reveling the secrets of their own complexity and patterns with valuable and critical, but challenging, issues through newly designed tools, techniques and models i…
This thesis is aimed at discovering new learning algorithms inspired by principles of biological evolution, which are able to exploit relational and contextual information, viewing clustering and classification problems in a dynamical system perspective. In pa…
Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for captu…
[EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged…
Automatic Text Classification (ATC) is one of the most important tasks in data mining for organizing information and knowledge discovery. The goal of ATC is to alleviate the need of manually organizing large collections of text documents, which is done by assi…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
