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for causal discovery and feature selection for classification part i: algorithms and empirical evaluation[J]. Journal of Machine Learning Research, 2010, 11(1): 171-234. [7] ZHANG Minling, PENA J M, ROBLES V. Feature selection for multi-label naive Bayes classification[J]. Information Sciences, 2009, 179(19): 3218-3229. [8] MALDONADO S, WEBER R, FAMILI F. Feature selection for high-dimensional class......
such as STL and SLC do not have a structure for storing feature data [7,8]. To overcome this, a classification of features based on principal curvatures was illustrated by LEFEBVRE and LAUWERS [9], which was then used by VERBERT et al [10] to define a feature based accuracy improvement methodology, FSPIF, for incremental forming. In this classification, four different feature types, planes, ruled surfaces......
. [8] YANG Meng, ZHANG Lei, SHIU S C K, et al. Gabor feature based robust representation and classification for face recognition with Gabor occlusion dictionary[J]. Pattern Recognition, 2013, 46(7...: 471-478. [12] LIU Chengjun, WECHSLER H. Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition[J]. IEEE Transactions on Image Processing, 2002, 11(4......
Feature dimensionality reduction of wear particle images based on semi-supervised locality preserving projection ZHANG Yunqiang, ZHANG Peilin (Seventh Department, Ordnance Engineering College, Shijiazhuang... projection for feature dimensionality reduction of wear particles, a semi-supervised locality preserving projection algorithm(PSS-LPP) based on Parzen windows and pairwise constrains was proposed. Parzen......
a revolution of the tool. The change of force direction causes the cutting dynamics to be unstable which results in chatter vibration. Therefore, cutting force signal monitoring and classification... with the back-propagation algorithm for monitoring and detecting abnormal state, and self organizing feature map (SOFM) for treating huge datum such as image processing and pattern recognition, for predicting......
Automatic web services classification based on rough set theoryCHEN Li(陈立)1, 2, ZHANG Ying(张英)1, 3, SONG Zi-lin(宋自林)1, MIAO Zhuang(苗壮)1(1. Institute of Command Automation, PLA University of Science... of existing services in the internet is growing day by day. In order to achieve automatic and accurate services classification which can be beneficial for service related tasks, a rough set theory based method......
. Thus SVM classifiers show better classification performance. Key words: support vector machine; wavelet packet analysis; feature extraction; fault diagnosis; multiple fault classifiers  ... fault diagnosis based on support vector machine(SVM) was put forward, in which wavelet packet analysis and signal energy decomposition were used for the feature extraction machinery faults. According......
Processing, 2003, 17(2): 317-328. [3] Arnaz M, Robert X G. PCA-based feature selection scheme for machine defect classification[J]. IEEE Transactions on Instrumentation and Measurement, 2004, 53(6): 1517-1525...码:A 文章编号:1672-7207(2011)11-3384-08 Mixed-domain feature extraction approach to rolling bearings faults based on kernel principle component analysis PENG......
technologies and read-depth analysis) with modern machine learning algorithms, using the recipe of feature extraction as a bridge. Compared with the state-of-art split-read methods for deletion detection in both...; false discovery rate; feature extraction; machine learning 1 Introduction A deletion is a kind of genomic alteration that a segment of DNA is missing in comparison with a reference genome. As one......
J. Cent. South Univ. (2020) 27: 3090-3102 DOI: https://doi.org/10.1007/s11771-020-4531-7 A-BQ, a classification system for anisotropic rock mass based on China National Standard GUO Song-feng(郭松峰)1... on China National Standard of BQ, named as A-BQ, is developed to address the classification of anisotropic rock mass incorporating the anisotropy degree as well as the quality of rock mass. Two series......