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...

The paper presents aspects regarding genetic algorithms, their use in data mining and especially about their use in the discovery of classification rules. A synthetic presentation of the fitness functions of the genetic algorithms used for mining the classification rules is performed. A genetic algorithm with a new fitness function for mining the classification rules is suggested. The proposed ...

The way we represent intentions, behaviors, and the spatial context, is crucial for any approach to mobile intention recognition. Formal grammars are cognitively comprehensible and make expressiveness properties explicit. By adding spatial domain knowledge to a grammar we can reduce parsing ambiguities. We argue that there are a number of mobile intention recognition problems which require the ...

Th e multiplicity of policies proposed to support the informal sector refl ects the lack of a common defi nition. Although they may produce positive eff ects, these are limited and fail to constitute a comprehensive strategic approach. Th e diff erent interpretations in the absence of a common defi nition as well as the strategies emerging from them are reviewed. Th e identifi cation of informa...

In medical field doctors need available information for decision making. Now day’s data mining method is applied in medical research in order to analyze large volume of medical data. This study attempts to use data mining method to analyze the database of diabetes and used for diagnosing for archiving better result. so this paper focus on analysis of diabetes data by various data mining techniq...

In this paper we present the performance analysis of different data mining techniques to predict the inpatient hospital length of stay in a super specialty hospital. Data set used for the analysis is real time data taken from super specialty hospital. Pre-processed data set is generated from the electronic discharge summaries obtained from the hospital. This data set consists of 401 records wit...

Classification is a supervised learning approach, which maps a data item into predefined classes. There are various classification algorithms proposed in the literature. In this paper authors have used four classification algorithms such as J48, Random Forest (RF), Reduce Error Pruning (REP) and Logistic Model Tree (LMT) to classify the "WEATHER NOMINAL" open source Data Set. Waikato ...