Early diagnosis is crucial to prevent the development of a disease that may cause danger human lives. COVID-19, which contagious has mutated into several variants, become global pandemic demands be diagnosed as soon possible. With use technology, available information concerning COVID-19 increases each day, and extracting useful from massive data can done through mining. In this study, authors ...

This paper presents three data mining techniques applied on a SCADA system data repository: Näıve Bayes, k-Nearest Neighbor and Decision Trees. A conclusion that k-Nearest Neighbor is a suitable method to classify the large amount of data considered is made finally according to the mining result and its reasonable explanation. The experiments are built on the training data set and evaluated usi...

This report summarizes the results of our work on trying to predict the health of a baby. We used two different machine learning algorithms, Weka and our own Naive Bayes Classifier. We discovered that placental ratio and Term/Preterm Birth yield interesting results, based on our list of 19 features. While the placental ratio results are puzzling, we learned that the two features Eclampsia and C...

Planning based on propositional satisfiability is a powerful approach for computing makespan-optimal plans. However, it is usually slower then heuristic-based sub-optimal approaches. In this work we propose MacroSatPlan; a SatPlan based planner which exploits macros extracted by Macro-FF and uses a predictive model of the optimal solution length that is constructed by WEKA, a commonly used tool...

Resumen En el presente trabajo se desarrolla un modelo para resolver el problema de similitud semántica entre textos de diferente longitud. Se propone extraer caracteŕısticas léxicas, caracteŕısticas basadas en conocimiento y caracteŕısticas basadas en corpus, con el objetivo de desarrollar un modelo de aprendizaje supervisado. El modelo fue desarrollado utilizando regresión loǵıstica de la her...

Multi-label classification has rapidly attracted interest in the machine learning literature, and there are now a large number and considerable variety of methods for this type of learning. We present Meka: an open-source Java framework based on the well-known Weka library. Meka provides interfaces to facilitate practical application, and a wealth of multi-label classifiers, evaluation metrics,...

With an advance in technologies, different tumor features have been collected for Breast Cancer (BC) diagnosis, processing of dealing with large data set suffers some challenges which include high storage capacity and time require for accessing and processing. The objective of this paper is to classify BC based on the extracted tumor features. To extract useful information and diagnose the tumo...

In the Natural Language Processing (NLP) community, Word Sense Disambiguation (WSD) has been described as the task which selects the appropriate meaning (sense) to a given word in a text or discourse where this meaning is distinguishable from other senses potentially attributable to that word. These senses could be seen as the target labels of a classification problem. Clustering and classifica...