A multiseed-based SVM classification technique for training sample reduction
نویسندگان
چکیده
منابع مشابه
Neighborhood based sample and feature selection for SVM classification learning
Support vector machines (SVMs) are a class of popular classification algorithms for their high generalization ability. However, it is time-consuming to train SVMs with a large set of learning samples. Improving learning efficiency is one of most important research tasks on SVMs. It is known that although there are many candidate training samples in some learning tasks, only the samples near pla...
متن کاملSVM Based Classification Technique for Color Image Retrieval
Due to digitization of technology there is a large volume digital images available. In recent years, CBIR is a research field which includes quickly search field of images from large database. Among all the types available of CBIR technology, color based image retrieval is growing area of interest. The technique mentioned in this paper is to develop Support Vector Machine based classification s...
متن کاملA new classification method based on pairwise SVM for facial age estimation
This paper presents a practical algorithm for facial age estimation from frontal face image. Facial age estimation generally comprises two key steps including age image representation and age estimation. The anthropometric model used in this study includes computation of eighteen craniofacial ratios and a new accurate skin wrinkles analysis in the first step and a pairwise binary support vector...
متن کاملA novel classification technique based on progressive transductive SVM learning
The existing semisupervised techniques based on progressive transductive support vector machine (PTSVM) iteratively select transductive samples that are closest to the SVM margin bounds. This may result in selecting wrong patterns (i.e., patterns that when included in the semisupervised learning can be associated with a wrong label) as transductive samples, especially when poor initial training...
متن کاملTraffic Prediction Based on SVM Training Sample Divided by Time
In recent years, the volume of traffic is rapidly increasing. When vehicles running through the tunnel are more intensive or move slowly, the tunnel environment occurs deteriorated sharply, which affects the normal operation of the vehicle in the tunnel. This paper uses the result of previous mining association rules to select feature items and to establish four training samples divided by time...
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: 2019
ISSN: 1303-6203
DOI: 10.3906/elk-1801-157