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检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"
3281 条 记 录,以下是2361-2370 订阅
排序:
Semi-Supervised Stream Clustering Using Labeled data Points  11th
Semi-Supervised Stream Clustering Using Labeled Data Points
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11th international conference on machine learning and data mining (MLDM)
作者: Treechalong, Kritsana Rakthanmanon, Thanawin Waiyamai, Kitsana Kasetsart Univ Dept Comp Engn Bangkok Thailand
Semi-supervised stream clustering performs cluster analysis of data streams by exploiting background or domain expert knowledge. Almost of existing semi-supervised stream clustering techniques exploit background knowl... 详细信息
来源: 评论
Decision Tree: Review of Techniques for Missing Values at Training, Testing and Compatibility  3
Decision Tree: Review of Techniques for Missing Values at Tr...
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3rd international conference on Artificial Intelligence, Modelling and Simulation (AIMS)
作者: Gavankar, Sachin Sawarkar, Sudhirkumar Mumbai Univ Datta Meghe Coll Engn Dept Comp Engn Navi Mumbai India
data mining rely on large amount of data to make learning model and the quality of data is very important. One of the important problem under data quality is the presence of missing values. Missing values can occur in... 详细信息
来源: 评论
3rd international Workshop on Similarity-Based pattern recognition, SIMBAD 2015
3rd International Workshop on Similarity-Based Pattern Recog...
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3rd international Workshop on Similarity-Based pattern recognition, SIMBAD 2015
The proceedings contain 16 papers. The special focus in this conference is on Similarity-Based pattern recognition. The topics include: A novel data representation based on dissimilarity increments;characterizing mult...
来源: 评论
Window-Based Feature Extraction Framework for Multi-Sensor data: A Posture recognition Case Study
Window-Based Feature Extraction Framework for Multi-Sensor D...
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3rd international conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated conference on Computer Science and Information Systems (FedCSIS)
作者: Grzegorowski, Marek Stawicki, Sebastian Univ Warsaw Fac Math Informat & Mech Banacha 2 PL-02097 Warsaw Poland
The article introduces a novel mechanism for automatic extraction of features from streams of numerical data. It was originally designed for the purpose of processing multiple streams of readings generated by sensors ... 详细信息
来源: 评论
IKLTSA: An Incremental Kernel LTSA Method  11th
IKLTSA: An Incremental Kernel LTSA Method
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11th international conference on machine learning and data mining (MLDM)
作者: Tani, Chao Guan, Jihong Zhou, Shuigeng Nanjing Normal Univ Sch Comp Sci & Technol Nanjing Jiangsu Peoples R China Tongji Univ Dept Comp Sci & Technol Shanghai 200092 Peoples R China Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China
Since 2000, manifold learning methods have been extensively studied, and demonstrated excellent performance in dimensionality reduction in some application scenarios. However, they still have some drawbacks in approxi... 详细信息
来源: 评论
learning Prior Bias in Classifier  3rd
Learning Prior Bias in Classifier
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3rd international conference on pattern recognition Applications and Methods (ICPRAM)
作者: Kobayashi, Takumi Nishida, Kenji Natl Inst Adv Ind Sci & Technol 1-1-1 Umezono Tsukuba Ibaraki Japan
In pattern classification, a classifier is generally composed both of feature (vector) mapping and bias. While the mapping function for features is formulated in either a linear or a non-linear (kernel-based) form, th... 详细信息
来源: 评论
Audio Recorder Forensic Identification in 21 Audio Recorders  3
Audio Recorder Forensic Identification in 21 Audio Recorders
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3rd IEEE international conference on Progress in Informatcs and Computing (IEEE PIC)
作者: Zeng, Jinhua Shi, Shaopei Yang, Xu Li, Yan Lu, Qimeng Qiu, Xiulian Zhu, Huaping Minist Justice Inst Forens Sci Shanghai 200063 Peoples R China Tongji Univ Coll Civil Engn Shanghai Peoples R China
Audio recorder forensic identification is to determine originating devices of questioned audio recordings. In this paper, statistical features both in time and frequency domains were studied and were used to represent... 详细信息
来源: 评论
Kernel Matrix Completion for learning Nearly Consensus Support Vector machines  3rd
Kernel Matrix Completion for Learning Nearly Consensus Suppo...
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3rd international conference on pattern recognition Applications and Methods (ICPRAM)
作者: Lee, Sangkyun Poelitz, Christian Tech Univ Dortmund Fak Informat LS 8 D-44221 Dortmund Germany
When feature measurements are stored in a distributed fashion, such as in sensor networks, learning a support vector machine (SVM) with a full kernel built with accessing all features can be pricey due to required com... 详细信息
来源: 评论
A Bayesian Approach to Sparse learning-to-Rank for Search Engine Optimization  11th
A Bayesian Approach to Sparse Learning-to-Rank for Search En...
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11th international conference on machine learning and data mining (MLDM)
作者: Krasotkina, Olga Mottl, Vadim RAS Ctr Comp Moscow 117901 Russia
Search engine optimization (SEO) is the process of affecting the visibility of a web page in the engine's search results. SEO specialists must understand how search engines work and which features of the web-page ... 详细信息
来源: 评论
A Systematic Comparison and Evaluation of Supervised machine learning Classifiers Using Headache dataset  11th
A Systematic Comparison and Evaluation of Supervised Machine...
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11th international conference on Intelligent Computing (ICIC)
作者: Aljaaf, Ahmed J. Al-Jumeily, Dhiya Hussain, Abir J. Fergus, Paul Al-Jumaily, Mohammed Radi, Naeem Liverpool John Moores Univ Appl Comp Res Grp Liverpool L3 3AF Merseyside England Dr Sulaiman Habib Hosp Dept Neurosurg Dubai Healthcare City U Arab Emirates Al Khawarizmi Int Coll Abu Dhabi U Arab Emirates
The massive growth of data volume within the healthcare sector pushes the current classical systems that were adapted to the limit. Recent studies have focused on the use of machine learning methods to develop healthc... 详细信息
来源: 评论