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» Robust Classification with Context-Sensitive Features
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CIKM
2009
Springer
13 years 11 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...
WWW
2010
ACM
13 years 7 months ago
Cross-domain sentiment classification via spectral feature alignment
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditio...
Sinno Jialin Pan, Xiaochuan Ni, Jian-Tao Sun, Qian...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
CIVR
2004
Springer
149views Image Analysis» more  CIVR 2004»
13 years 11 months ago
A Framework for Semantic Classification of Scenes Using Finite State Machines
We address the problem of classifying scenes from feature films into semantic categories and propose a robust framework for this problem. We propose that the Finite State Machines ...
Yun Zhai, Zeeshan Rasheed, Mubarak Shah
ICMCS
2005
IEEE
138views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Overcomplete ICA-based Manmade Scene Classification
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
Matthew Boutell, Jiebo Luo