In this paper, we study the performance criterion of machine learning tools in classifying breast cancer. We compare the data mining tools such as Naïve Bayes, Support vector machines, Radial basis neural networks, Decision trees J48 and simple CART. We used both binary and multi class data sets namely WBC, WDBC and Breast tissue from UCI machine learning depositary. The experiments are conduct...

Data mining is an iterative progress in which evolution is defined by detection, through usual or manual methods. The discovered knowledge can be used for different applications for example healthcare industry. The heart disease accounts to be the leading cause of death worldwide. It is difficult for medical practitioners to predict the heart attack as it is complex task that requires experienc...

The main objective of any educational organization is to provide quality education and improve the overall performance of an institution by looking at individual performances. One way to analyze learners' performances is to identify the areas of weakness and guide their students to a better future. Although data mining has been successful in many areas, its use in student performance analysis i...

Holdup in Oligopsonistic Labour Markets: A New Role for the Minimum Wage We consider a labour market model of oligopsonistic wage competition and show that there is a holdup problem although workers do not have any bargaining power. When a firm invests more, it pays a higher wage in order to attract workers from competitors. Because workers participate in the returns on investment while only fi...

Activity recognition has become the necessity of smart homes, future factories, and surveillance. Activities independent of body posture predominantly exhibiting gestures involving both arm and the wrist motion supports the use of the wearable sensors for data acquisition. This paper uses an algorithm based prediction method to recognize the Activities of Daily Life (ADL) involving activities l...

Fault diagnosis of monoblock centrifugal pump is conceived as a pattern recognition problem. There are three important phases involved in a pattern recognition namely feature extraction, feature selection and classification. In this study, stationary wavelet transform (SWT) is used for feature extraction and J48 algorithm is used for feature selection and classification. The different fault con...

Uterine fibroids are benign growths in the uterus, for which there are several possible treatment options. Patients and physicians generally approach the decision process based on a combination of the patient’s degree of discomfort, patient preferences, and physician practice patterns. In this paper, we examine the use of classification algorithms in combination with metalearning algorithms as ...

The application of data mining algorithms requires the use of powerful software tools. As the number of available tools continues to grow, the choice of the most suitable tool becomes increasingly difficult. This paper present the basic data mining techniques i. e. , naive Bayesian tree, RIpple DOwn Rule, naive Bayes and decision tree algorithm J48 for classifying in medical databases. The goal...

Cardiotocography (CTG) records fetal heart rate (FHR) and uterine contractions (UC) simultaneously. Cardiotocography trace patterns help doctors to understand the state of the fetus. Even after the introduction of cardiotocograph, the capacity to predict is still inaccurate. This paper evaluates some commonly used classification methods using WEKA. Precision, Recall, F-Measrue and ROC curve hav...

This paper describes a project to compare two feature classification algorithms used in activity recognition in relation to accelerometer and heart rate data. Data was collected from six male and female subjects using a single tri-axial accelerometer and heart monitor attached to each subject’s dominant thigh. Subjects carried out eight activities and the data was labelled semi-automatically. F...