This paper reports on the empirical evaluation of five machine learning algorithm such as J48, BayesNet, OneR, NB and ZeroR using ten performance criteria: accuracy, precision, recall, F-Measure, incorrectly classified instances, kappa statistic, mean absolute error, root mean squared error, relative absolute error, root relative squared error. The aim of this paper is to find out which classif...

Flash flooding is a type of global devastating hydrometeorological disaster that seriously threatens people’s property and physical safety, as well the normal operation water conservancy facilities, such reservoirs, so an accurate assessment reservoir risk for certain areas necessary. Therefore, purpose this study was to propose novel methodological approach modelling based on feature selection...

This paper proposed a method using principle component analysis based on graph entropy (PCA-GE) and J48 decision tree on electroencephalogram (EEG) signals to predict whether a person is alcoholic or not. Analysis is performed in two stages: feature extraction and classification. The principle component analysis (PCA) chooses the optimal subset of channels based on graph entropy technique and t...

Data mining is a technique that involves the application of specific algorithms, which generate a list of patterns based on large volumes of information that is useful for decision making in wide fields of application, as detection of patterns in diseases. This paper proposes to carry out a cancer analysis by means of data mining techniques, applied on a sample of 3365 cases, using association ...

The role of technology in education industry is increasing day by day specially after reaching the growth rate of the IT industry to the saturation point. That is why, even AICTE has closed the affiliation of engineering colleges in number of states. So, education industry can change their plan to survive in this environment by using data mining techniques to identify the outstanding students a...

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...

This paper introduces the speech emotion corpus, a multilingual speech emotion database recorded in the provincial languages of Pakistan: Urdu, Punjabi, Pashto and Sindhi for analyzing the speech emotions present in the recorded speech signals with the four different emotions (Anger, Sadness, Comfort and Happiness). The objective of this paper is to evaluate the performance of the learning clas...

In today’s world, gigantic amount of data is available in science, industry, business and many other areas. This data can provide valuable information which can be used by management for making important decisions. But problem is that how can find valuable information. The answer is data mining. Data Mining is popular topic among researchers. There is lot of work that cannot be explored till no...

Clustering and classification are two important techniques of data mining. Classification is a supervised learning problem of assigning an object to one of several pre-defined categories based upon the attributes of the object. While, clustering is an unsupervised learning problem that group objects based upon distance or similarity. Each group is known as a cluster. In this paper we make use o...

Software repositories with defect logs are main resource for defect prediction. In recent years, researchers have used the vast amount of data that is contained by software repositories to predict the location of defect in the code that caused problem. In this paper machine learning approach is used for predicting the modules with defect for embedded data set. Public datasets from the promise r...