SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis
نویسندگان
چکیده
In this paper, a new classification approach combining support vector machine with scatter search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach is used to find near optimal values of SVM parameters and its kernel parameters. The hepatitis dataset is obtained from UCI. Experimental results and comparisons prove that the 3SVM gives better outcomes and has a competitive performance relative to other published methods found in literature, where the average accuracy rate obtained is 98.75%. Keywords—Support Vector Machine; Scatter Search; Classification; Parameter tuning
منابع مشابه
A Novel Algorithm for Accurate Diagnosis of Hepatitis B and Its Severity
Background and Objectives: Accurate detection of type and severity of Hepatitis is crucial for effective treatment of the disease. While several computational algorithms for detection of Hepatitis have been proposed to date, their limited performance leaves room for further improvement. This paper proposes a novel computational method for the diagnosis of Hepatitis B using pattern detection tec...
متن کاملA new hybrid method based on local fisher discriminant analysis and support vector machines for hepatitis disease diagnosis
In this paper, a novel hybrid method named the LFDA_SVM, which integrates a new feature extraction method and a classification algorithm, has been introduced for diagnosing hepatitis disease. The two integrated methods are the local fisher discriminant analysis (LFDA) and the supporting vector machine (SVM), respectively. In the proposed LFDA_SVM, the LFDA is employed as a feature extraction to...
متن کاملA New Knowledge-Based System for Diagnosis of Breast Cancer by a combination of the Affinity Propagation and Firefly Algorithms
Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two groups of breast cancer patients (malignant and benign). The proposed approach, AP-AMBFA, con...
متن کاملA New Formulation for Cost-Sensitive Two Group Support Vector Machine with Multiple Error Rate
Support vector machine (SVM) is a popular classification technique which classifies data using a max-margin separator hyperplane. The normal vector and bias of the mentioned hyperplane is determined by solving a quadratic model implies that SVM training confronts by an optimization problem. Among of the extensions of SVM, cost-sensitive scheme refers to a model with multiple costs which conside...
متن کاملEpileptic Seizure Detection in EEG signals Using TQWT and SVM-GOA Classifier
Background: Epilepsy is a Brain disorder disease that affects people's quality of life. If it is diagnosed at an early stage, it will not be spread. Electroencephalography (EEG) signals are used to diagnose epileptic seizures. However, this screening system cannot diagnose epileptic seizure states precisely. Nevertheless, with the help of computer-aided diagnosis systems (CADS), neurologists ca...
متن کامل