Career success and its evaluation in university graduates generate growing interest the academy when evaluating according to mission social mandate. Therefore, monitoring is essential measuring career State Technical University of Quevedo (UTEQ, acronym Spanish). In this sense, article aims identify predictive factors through survey application, development two mathematical functions, Weka’s cl...

Predicting the structural condition of sewer pipes plays a vital role in predictive maintenance and renewal plans many water utilities. This study explores simultaneous utilization physical environmental features prediction. Three (3) hybrid machine learning models which are combination Bagging (BG), Dagging (DG), Rotation Forest (RotF) ensembles with J48 Decision Tree (J48DT) based classifier ...

When predictive modeling requires comprehensible models, most data miners will use specialized techniques producing rule sets or decision trees. This study, however, shows that genetically evolved decision trees may very well outperform the more specialized techniques. The proposed approach evolves a number of decision trees and then uses one of several suggested selection strategies to pick on...

Decision tree models are commonly used in educational data mining to examine the data and induce a tree that will be used to make predictions about educational data. This study enables to obtain the decision tree models that predict the academic performance of the engineering students in contact education system. Genetic algorithm is a powerful search and optimization technique that has shown p...

BACKGROUND AND PURPOSE The prediction of prognosis in HGGs is poor in the majority of patients. Our aim was to test whether multivariate prediction models constructed by machine-learning methods provide a more accurate predictor of prognosis in HGGs than histopathologic classification. The prediction of survival was based on DTI and rCBV measurements as an adjunct to conventional imaging. MAT...

Data mining is the upcoming research area to solve various problems and classification is one of main problem in the field of data mining. In this paper, we use two classification algorithms J48 (which is java implementation of C4. 5 algorithm) and multilayer perceptron alias MLP (which is a modification of the standard linear perceptron) of the Weka interface. It can be used for testing severa...

Educational data mining concerns with developing the methods for discovering knowledge from data that come from educational environment. In this paper we used educational data mining to analyze learning behavior of modern students. In our case study, we collected students' data from a higher education institution in terms of the mentioned attributes. After preprocessing the data, we applied dat...

Machine Learning focuses on the construction and study of systems that can learn from data. This is connected with the classification problem, which usually is what Machine Learning algorithms are designed to solve. When a machine learning method is used by people with no special expertise in machine learning, it is important that the method be ‘robust’ in classification, in the sense that reas...

Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new techn...

A lot of time is spent searching for the most performing data mining algorithms applied in clinical diagnosis. The study set out to identify the most performing predictive data mining algorithms applied in the diagnosis of Erythemato-squamous diseases. The study used Naive Bayes, Multilayer Perceptron and J48 decision tree induction to build predictive data mining models on 366 instances of Ery...