Most decision-tree induction algorithms are using a local greedy strategy, where a leaf is always split on the best attribute according to a given attribute selection criterion. A more accurate model could possibly be found by looking ahead for alternative subtrees. However, some researchers argue that the look-ahead should not be used due to a negative effect (called ―decision tree pathology‖)...

Network traffic recognition serves as a basic condition for network operators to differentiate and prioritize number of purposes, from guaranteeing the Quality Service (QoS), monitoring safety, well detecting anomalies. Web Real-Time Communication (WebRTC) is an open-source project that enables real-time audio, video, text communication among browsers. Since WebRTC does not include any characte...

Data mining has become one of the emerging fields in research because of its vast contents. Data mining is used for finding hidden patterns in the database or any other information repository. This information is necessary to generate knowledge from the patterns. The main task is to extract knowledge out of the information. In this paper we use a data mining technique called classification to d...

The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and...

Now a days, the Data Engineering becoming emerging trend to discover knowledge from web audiovisual data such asYouTube videos, Yahoo Screen, Face Book videos etc. Different categories of web video are being shared on such social websites and are being used by the billions of users all over the world. The uploaded web videos will have different kind of metadata as attribute information of the v...

The use of ensemble of classifiers for classification of medical data derived from diagnostic devices has been proposed in this research. The experimental studies were carried out on three datasets concerning different medical problems: arrhythmia, breast cancer and coronary artery disease using SPECT images. The comparison of single classification algorithms (kNNIBk, C4.5 J48, Naïve Bayes, Ran...

Data mining which involves systematic analyses of large datasets for extracting the knowledge. Classification is considered as one of the major basic research topics that manage the data. Due to the rapid developments in microarray technology and it offer the capability to measure expression levels of thousands of genes simultaneously. study of such data helps us discovering different clinical ...

in the present study, classification trees (cts-j48 algorithm) were used to study the occurrence of roach in rivers in flanders (belgium). the presence/absence of roach was modelled based on a set of river characteristics. the predictive performance of the cts models was assessed based on the percentage of correctly classified instances (cci) and cohen's kappa statistics. to find the best model...

Clinical studies in the past have shown that the pathology of Alzheimer’s disease (AD) initiates, 10 to 15 years before the visible clinical symptoms of cognitive impairment starts to appear in AD diagnosed patients. Therefore, early diagnosis of the AD using potential early stage cerebrospinal fluid (CSF) biomarkers will be valuable in designing a clinical trial and proper care of AD patients....

In this work are evaluated features selection methods for breast cancer classification in segmented mammographic lesions using two categories of extracted features (numeric and nominal). Numeric included statistical, shape and texture lesion descriptors, and nominal are related with patient’s associated metadata descriptors (clinical history). Datasets of features vectors were created using six...