Search Results - "2006 5th International Conference on Machine Learning and Applications (ICMLA'06)"

TF-ICF: A New Term Weighting Scheme for Clustering Dynamic Data Streams by Reed, J.W., Jiao, Yu, Potok, T.E., Klump, B.A., Elmore, M.T., Hurson, A.R.

“…In this paper, we propose a new term weighting scheme called term frequency-inverse corpus frequency (TF-ICF). It does not require term frequency information…”
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Horizon Detection Using Machine Learning Techniques by Fefilatyev, S., Smarodzinava, V., Hall, L.O., Goldgof, D.B.

“…Detecting a horizon in an image is an important part of many image related applications such as detecting ships on the horizon, flight control, and port…”
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Reducing High-Dimensional Data by Principal Component Analysis vs. Random Projection for Nearest Neighbor Classification by Deegalla, S., Bostrom, H.

“…The computational cost of using nearest neighbor classification often prevents the method from being applied in practice when dealing with high-dimensional…”
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Supernova Recognition Using Support Vector Machines by Romano, R.A., Aragon, C.R., Ding, C.

“…We introduce a novel application of support vector machines (SVMs) to the problem of identifying potential supernovae using photometric and geometric features…”
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Naive Bayes Classification Given Probability Estimation Trees by Zengchang Qin

“…Tree induction is one of the most effective and widely used models in classification. Unfortunately, decision trees such as C4.5 have been found to provide…”
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Shape Recognition and Retrieval Using String of Symbols by Daliri, M.R., Torre, V.

“…In this paper we present two algorithms for shape recognition. Both algorithms map the contour of the shape to be recognized into a string of symbols. The…”
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Learning the Threshold in Hierarchical Agglomerative Clustering by Daniels, K., Giraud-Carrier, C.

“…Most partitional clustering algorithms require the number of desired clusters to be set a priori. Not only is this somewhat counter-intuitive, it is also…”
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A Fast Feature Selection Model for Online Handwriting Symbol Recognition by Huang, B.Q., Kechadi, M.-T.

“…Many feature selection models have been proposed for online handwriting recognition. However, most of them require expensive computational overhead, or…”
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Detecting Web Content Function Using Generalized Hidden Markov Model by Chen, Jinlin, Zhong, Ping, Cook, Terry

“…Web content function indicates authors' intension towards the purpose of the content and therefore plays an important role for Web information processing. In…”
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Ensemble Classifiers for Medical Diagnosis of Knee Osteoarthritis Using Gait Data by Koktas, N.S., Yalabik, N., Yavuzer, G.

“…Automated or semi-automated gait analysis systems are important in assisting physicians for diagnosis of various diseases. The objective of this study is to…”
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Off-Line Signature Recognition and Verification by Kernel Principal Component Self-Regression by Zhang, B.-L.

“…Automatic signature verification is an active area of research with numerous applications such as bank check verification, ATM access, etc. In this research, a…”
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Preface

“…Presents the welcome message from the conference proceedings…”
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Information of Binding Sites Improves Prediction of Protein-Protein Interaction by Patel, T., Pillay, M., Jawa, R., Liao, L.

“…Protein-protein interaction is essential to cellular functions. In this work, we describe a simple, novel approach to improve the accuracy of predicting…”
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An Intelligent Automatic Fingerprint Recognition System Design by Ozkaya, N., Sagiroglu, S., Wani, A.

“…This work presents an intelligent automatic fingerprint identification and verification system based on artificial neural networks. In this work, the design…”
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An Approximate Version of Kernel PCA by Martin, S.

“…We propose an analog of kernel principal component analysis (kernel PCA). Our algorithm is based on an approximation of PCA which uses Gram-Schmidt…”
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Two-Level Hierarchical Hybrid SVM-RVM Classification Model by Silva, C., Ribeiro, B.

“…Support vector machines (SVM) and relevance vector machines (RVM) constitute two state-of-the-art learning machines that are currently focus of cutting-edge…”
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Incremental Learning By Decomposition by Bouchachia, A.

“…Adaptivity in neural networks aims at equipping learning algorithms with the ability to self-update as new training data becomes available. In many…”
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An Adaptable Time Warping Distance for Time Series Learning by Gaudin, R., Nicoloyannis, N.

“…Most machine learning and data mining algorithms for time series datasets need a suitable distance measure. In addition to classic p-norm distance, numerous…”
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Market Mechanism Designs with Heterogeneous Trading Agents by Zengchang Qin

“…Market mechanism design research is playing an important role in computational economics for resolving multi-agent allocation problems. A genetic algorithm was…”
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A Comparison of Software Fault Imputation Procedures by Hulse, Jason Van, Khoshgoftaar, Taghi M., Seiffert, Chris

“…This work presents a detailed comparison of three imputation techniques, Bayesian multiple imputation, regression imputation and k nearest neighbor imputation,…”
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