Radial basis function network

Abstract— In this paper, an approach for gender classification is carried out combining frontal face images, Haar cascades, Histogram of Oriented Gradients and Support Vector Machines. The comparison of the existing methods that delves into the effects of Haar Cascade Classifier and Histogram of Oriented Gradients(HOG) for Face Detection and the use of Support Vector Machines(SVM) for Gender Classification. A database of 2-D facial images was used, consisting of individual as well as group photographs

including working memory, executive function, attention and information processing are defective.Deficits are observed in multiple domains, including working memory, executive function, attention and information processing. Disability caused by cognitive dysfunction are is frequently as debilitating as the prominent emotional disturbances. Interactions between the hippocampus and the prefrontal cortex are

A system to delete unwanted messages from osn use walls abstract One principal issue in today On-line Social Networks (OSNs) is to give clients the capacity to control the messages posted naturally private space to stay away from that undesirable substance is shown. Up to now OSNs give little backing to this prerequisite. To fill the crevice, in this paper, we propose a framework permitting OSN clients to have an immediate control on the messages posted on their dividers. This is

POWER QUALITY ENHANCEMENT FOR REAL AND REACTIVE POWER COORDINATION IN AUTONOMOUS MICRO GRIDS OPERATION USING PSO UPFC S. Niveditha P.G Scholar Dept of Electrical and Electronics Engineering SRKR Engineering College Bhimavaram, India. niveditha.sdm@gmail.com B. Mothi Ram M.Tech Asst.Professor Dept of Electrical and Electronics Engineering SRKR Engineering

2. Project statement 5 2.1. Problem definition 5 2.2. Project objective 6 3. Data description and preprocessing 8 3.1. Data description 8 3.2. Data preprocessing 9 4. Data mining techniques 12 4.1 Linear Regression 12 4.2 Neural Network 13 4.3 Support Vector Machine 14 4.4 K-fold cross validation 15 4.5 Performance Evaluation 16 5. Analysis Process 17 5.1 Feature selection 17

Theoretical and Applied Information Technology 10th May 2016. Vol.87. No.1 © 2005 - 2016 JATIT & LLS. All rights reserved. ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 1 A COMPUTATIONAL HYBRID MODEL WITH TWO LEVEL CLASSIFICATION USING SVM AND NEURAL NETWORK FOR PREDICTING THE DIABETES DISEASE 1NASIB SINGH GILL, 2 POOJA MITTAL 1 Professor, Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, Haryana, India 2 Assistant Professor, Department of Computer Science & Applications

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population and generates an instantaneous city. Its extensions include the TOMM (considers the time element) and BASS (focuses on housing markets) models. Later, the ITLUP model has been proposed to integrate a Lowry-type sub-model with a transportation network assignment sub-model. Recent work has concentrated on combining spatial interaction factors with an econometric model, starting with Steinnes’ and Fisher’s analysis of the relationship7 between population and jobs at the metropolitan level. Carlino

International Journal of Management & Information Systems – Third Quarter 2010 Volume 14, Number 3 Decision Tree Induction & Clustering Techniques In SAS Enterprise Miner, SPSS Clementine, And IBM Intelligent Miner – A Comparative Analysis Abdullah M. Al Ghoson, Virginia Commonwealth University, USA ABSTRACT Decision tree induction and Clustering are two of the most prevalent data mining techniques used separately or together in many business applications. Most commercial data mining software

1 Introduction 1.1 The research question This literature review has been undertaken as part of research into detecting early Parkinson’s Disease (PD) through the characteristics of finger movement during typing. It begins with a discussion of PD and its symptoms, and then provides an overview of the current and emerging diagnostic strategies for early detection of the disease, with particular emphasis on those involving human-computer interaction (HCI) and the relationship with keystroke biometrics