10. Version spaces, neural networks, and Analogical Modeling

Chapters in this book

1. Prelim pages i
2. Table of contents v
3. List of contributors ix
4. Introduction 1
5. Part I. The basics of Analogical Modeling
6. 1. An overview of Analogical Modeling 11
7. 2. Issues in Analogical Modeling 27
8. Part II. Psycholinguistic evidence for Analogical Modeling
9. 3. Skousen’s analogical approach as an exemplar-based model of categorization 51
10. Part III. Applications to specific languages
11. 4. Applying Analogical Modeling to the German plural 109
12. 5. Testing Analogical Modeling 123
13. Part IV. Comparing Analogical Modeling with TiMBL
14. 6. A comparison of two analogical models 141
15. 7. A comparison of Analogical Modeling to Memory-Based Language Processing 157
16. 8. Analogical hierarchy 181
17. Part V. Extending Analogical Modeling
18. 9. Expanding k -NN analogy with instance families 209
19. 10. Version spaces, neural networks, and Analogical Modeling 225
20. 11. Exemplar-driven analogy in Optimality Theory 265
21. 12. The hope for analogous categories 301
22. Part VI. Quantum computing and the exponential explosion
23. 13. Analogical Modeling and quantum computing 319
24. Part VII. Appendix
25. 14. Data files for Analogical Modeling 349
26. 15. Running the Perl/C version of the Analogical Modeling program 365
27. 16. Implementing the Analogical Modeling algorithm 385
28. Index 411