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IFT6255: Information Retrieval Text classification

IFT6255: Information Retrieval Text classification

IFT6255: Information Retrieval Text classification. Overview. Definition of text classification Important processes in classification Classification algorithms Advantages and disadvantages of algorithms Performance comparison of algorithms Conclusion. Text Classification.

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828 views • 50 slides
Sentiment analysis of microblogging data using sentiment lexicons as noisy labels

Sentiment analysis of microblogging data using sentiment lexicons as noisy labels

Sentiment analysis of microblogging data using sentiment lexicons as noisy labels. By OLUGBEMI Eric ODUMUYIWA Victor OKUNOYE Olusoji. OUTLINE. OBJECTIVES OF THE STUDY RESEARCH QUESTIONS SIGNIFICANCE OF THE STUDY MACHINE LEARNING SUPERVISED MACHINE LEARNING

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715 views • 24 slides
Friday, 05 November 2004 William H. Hsu Department of Computing and Information Sciences, KSU

Friday, 05 November 2004 William H. Hsu Department of Computing and Information Sciences, KSU

Lecture 32 of 41. Applications 2 of 3: Machine Translation and Language Learning. Friday, 05 November 2004 William H. Hsu Department of Computing and Information Sciences, KSU http://www.kddresearch.org http://www.cis.ksu.edu/~bhsu Readings: Reference: Sections 6.9-6.10, Mitchell.

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460 views • 24 slides
An Automated Classification Algorithm for Multi-wavelength Data

An Automated Classification Algorithm for Multi-wavelength Data

LAMOST. An Automated Classification Algorithm for Multi-wavelength Data. Yanxia Zhang, Ali Luo,Yongheng Zhao National Astronomical Observatories, China 2005.8.16, Lijiang. ROSAT ~keV. DSS Optical. IRAS 25 m. 2MASS 2 m. GB 6cm. WENSS 92cm. NVSS 20cm. IRAS 100 m. Astronomy facing

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222 views • 11 slides

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