Study the behavior of malicious software, understand the security challenges, detect the malware behavior automatically using dynamic approach. Study various classification techniques and to group these malwares and able to cluster different malware into unknown group whose characteristics are not known. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and...

as we know that with the help of Data mining techniques we can find out knowledge in terms of various characteristics and patterns. In this regard this paper presents finding out of anomalies/ outliers using various decision tree based classifiers viz. Best-first Decision Tree, Functional Tree, Logistic Model Tree, J48 and Random Forest decision tree. Three real world datasets has been used in ...

In this paper different classification techniques of Data Mining are compared using diverse datasets from University of California, Irvine(UCI). Accuracy and time required for execution by each technique is observed. The Data Mining refers to extracting or mining knowledge from huge volume of data. Classification is an important data mining technique with broad applications. It classifies data ...

Twitter presents a new forum for spammers to facilitate illegal pharmaceutical scams. We present a classification scheme using decision strategy and data mining techniques taking into account the unbalanced nature of the data set. Four classifiers are used to identify pharmaceutical spam tweets. Classifiers J48 and Random Tree (RT) are generated by Weka tools, and classifiers DL(J48) and DL(RT)...

The application of data mining technique has been widely applied in different business areas such as health, education and finance for the purpose of data analysis and then to support and maximizes the organizations’ customer satisfaction in an effort to increase loyalty and retain customers’ business over their lifetimes . The researchers’ primary objective, in this paper is to classify custom...

the Paper presents the comparison of different classification techniques for the task of classifying Number plate image data set. The comparison was conducted using WEKA (Waikato Environment for Knowledge Analysis) open source which mainly consists the collection of machine learning algorithms for data mining purpose. The main purpose of this paper is to investigate efficiency of different clas...

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...

Classification is the most widely applied machine learning problem today, with implementations in face recognition, flower classification, clustering, and other fields. The goal of this paper to organize identify a set data objects. study employs K-nearest neighbors, decision tree (j48), random forest algorithms, then compares their performance using IRIS dataset. results comparison analysis sh...

Learning Disability (LD) is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. It is a classification including several disorders in which a child has difficulty learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. An affected child can have normal o...

Data mining techniques are widely used in classification and prediction in the field of bioinformatics to analyze biomedical data. The purpose of the study is to investigate and compare (7) different classification algorithms namely, Naive Bayes, Naive Bayes updatable, FT Tree, KStar, J48, LMT, and Neural network for analyzing Hepatitis prognostic data. The results of the classification are acc...