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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining

Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining

Ishibuchi, Hisao
Nakashima, Tomoharu
Nii, Manabu

Hardcover

Series: Advanced Information Processing

General ComputersGeneral Mathematics

ISBN10: 3540207678
ISBN13: 9783540207672
Publisher: Springer Nature
Published: Nov 19 2004
Pages: 308
Weight: 1.25
Height: 0.90 Width: 6.30 Depth: 9.30
Language: English
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod- els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe- matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com- puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter- net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model- ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

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