A novel semisupervised classification method via membership and polyhedral conic functions
نویسندگان
چکیده
منابع مشابه
Multi Class Classification with Polyhedral Conic Functions1
1. Mathematical model. 1.1. Multi objective integer programming model. A kmesindeki her a1, a2, . . . , am noktas iin kar gelen KF’ler srasyla g1, g2, . . . , gm olsun. Bu fonksiyonlarn elde edilmesinin ardndan, her fonksiyonun hangi noktalar ayrdn gsteren bir Pm×m matrisi, eer A kmesindeki i. nokta, ai, l. fonksiyon ile ayrlyor ise Pil = 1, dier durumda Pil = 0 olacak ekilde oluturulsun. Bu aa...
متن کاملExtracting Membership Functions Using ACS Method via Multiple Minimum Supports
Ant Colony Systems (ACS) have been successfully applied to different optimization issues in recent years. However, only few works have been done by employing ACS method to data mining. This paper addresses the lack of investigations on this study by proposing an ACS -based algorithm to extract membership functions in fuzzy data mining. In this paper, the membership functions were encoded into b...
متن کاملUnsupervised and Semisupervised Classification Via Absolute Value Inequalities
We consider the problem of classifying completely or partially unlabeled data by using inequalities that contain absolute values of the data. This allows each data point to belong to either one of two classes by entering the inequality with a plus or minus value. By using such absolute value inequalities (AVIs) in linear and nonlinear support vector machines, unlabeled or partially labeled data...
متن کاملOptimization of fuzzy membership functions via PSO and GA with application to quad rotor
Quad rotor is a renowned underactuated Unmanned Aerial Vehicle (UAV) with widespread military and civilian applications. Despite its simple structure, the vehicle suffers from inherent instability. Therefore, control designers always face formidable challenge in stabilization and control goal. In this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nat...
متن کاملA novel method based on a combination of deep learning algorithm and fuzzy intelligent functions in order to classification of power quality disturbances in power systems
Automatic classification of power quality disturbances is the foundation to deal with power quality problem. From the traditional point of view, the identification process of power quality disturbances should be divided into three independent stages: signal analysis, feature selection and classification. However, there are some inherent defects in signal analysis and the procedure of manual fe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES
سال: 2020
ISSN: 1303-6203
DOI: 10.3906/elk-1905-45