Relevance learning for mental disease classification
نویسندگان
چکیده
A b s t r a c t. fi c t r e a t m e n t a n d t h e r a p y m a n a g e m e n t i s n e c-e s s a r y f o r t h e s e p a t i e n t s [ 2 ]. T h i s c l a s s i fi c a t i o n h a s t o t a k e p l a c e b e f o r e t h e t r e a t m e n t .
منابع مشابه
Mental Arithmetic Task Recognition Using Effective Connectivity and Hierarchical Feature Selection From EEG Signals
Introduction: Mental arithmetic analysis based on Electroencephalogram (EEG) signal for monitoring the state of the user’s brain functioning can be helpful for understanding some psychological disorders such as attention deficit hyperactivity disorder, autism spectrum disorder, or dyscalculia where the difficulty in learning or understanding the arithmetic exists. Most mental arithmetic recogni...
متن کاملGeneralized functional relevance learning vector quantization
Generalized learning vector quantization (GRLVQ) is a prototype based classification algorithm with metric adaptation weighting each data dimensions according to their relevance for the classification task. We present in this paper an extension for functional data, which are usually very high dimensional. This approach supposes the data vectors have to be functional representations. Taking into...
متن کاملHow Effectiveness Of Comprehensive Performance Measurement Systems on Manager's Performance Through Modification of Mental Models (Learning Process)
One of the ways to reduce agency costs is to plan for the creation of effective decision-making information by designing appropriate comprehensive performance evaluation systems according to managers' learning process One of the important factors in the processing and classification of information for cognitive learning is mental models that are categorized in two dimensions of mental model co...
متن کاملA Random Forest Classifier based on Genetic Algorithm for Cardiovascular Diseases Diagnosis (RESEARCH NOTE)
Machine learning-based classification techniques provide support for the decision making process in the field of healthcare, especially in disease diagnosis, prognosis and screening. Healthcare datasets are voluminous in nature and their high dimensionality problem comprises in terms of slower learning rate and higher computational cost. Feature selection is expected to deal with the high dimen...
متن کاملبازیابی تعاملی تصاویر طبیعت با بهره گیری از یادگیری چند نمونه ای
Content-based image retrieval (CBIR) has received considerable research interest in the recent years. The basic problem in CBIR is the semantic gap between the high-level image semantics and the low-level image features. Region-based image retrieval and learning from user interaction through relevance feedback are two main approaches to solving this problem. Recently, the research in integra...
متن کاملInvestigating the Adoption Rate of Students' Mental Model with the Structure of the Learning Management System of the University of Tehran by Card Sorting Method
Background and Aim: E-learning is an important topic in the educational settings and students are significant prerequisites of it, who have an essential role for the acceptance and effective use of e-learning management systems so that knowing their attitudes and mental models is essential for the successful implementation of such a method. Therefore, the aim of this study was to investigate...
متن کامل