نتایج جستجو برای: sequential floating forward selection
تعداد نتایج: 532216 فیلتر نتایج به سال:
This paper developed a diagnosis model based on Support Vector Machines (SVM) with a novel hybrid feature selection method to diagnose erythemato-squamous diseases. Our hybrid feature selection method, named IFSFFS (Improved F -score and Sequential Forward Floating Search), combines the advantages of filters and wrappers to select the optimal feature subset from the original feature set. In our...
In this paper we suggest feature selection and Principal Component Analysis as a way to analyze and compare corpora of emotional speech. To this end, a fast improvement of the Sequential Forward Floating Search algorithm is introduced, and subsequently extensive tests are run on a selection of French emotional language resources well suited for a first impression on general applicability. Tools...
electroencephalogram (eeg) is one of the useful biological signals to distinguish different brain diseases and mental states. in recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from eeg signals. in this research, we introduce an emot...
In order to automatically evaluate the welding quality during high-power disk laser welding, a real-time monitoring system was developed. The images of laser-induced metal vapor during welding were captured and fifteen features were extracted. A feature selection method based on a sequential forward floating selection algorithm was employed to identify the optimal feature subset, and a support ...
Handwriting is individualistic. The uniqueness of shape and style of handwriting can be used to identify the significant features in authenticating the author of writing. Acquiring these significant features leads to an important research in Writer Identification domain where to find the unique features of individual which also known as Individuality of Handwriting. This paper proposes an impro...
Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...
A large number of algorithms have been proposed for doing feature subset selection. The goal of this paper is to evaluate the quality of feature subsets generated by the various algorithms, and also compare their computational requirements. Our results show that the sequential forward floating selection (SFFS) algorithm, proposed by Pudil et al., dominates the other algorithms tested. This pape...
In this paper we present an improved Sequential Forward Floating Search algorithm. Subsequently, extensive tests are carried out on a selection of French emotional language resources well suited for a first impression on general applicability. A detailed analysis is presented to test the various modifications suggested one-by-one. Our conclusion is that the modification in the forward step resu...
Automatic Detection And Classification (ADAC) is a system to detect and classify the underwater objects for mine hunting applications. The segmentation, feature extraction, and classification are the main steps involved in the system. Two design issues in the system, the selection of the optimal classifier and the selection of the optimal feature subset. The comparison of classification systems...
Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more than 75% - 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra-red...
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