| ISBN |
9789819939176 |
| 기타 표준번호 |
10.1007/978-981-99-3917-6 |
| 청구기호 |
Q325.5-.7 |
| 형태사항 |
XV, 532 p. 109 illus., 5 illus. in color. online resource.
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| 언어 |
English |
| 내용 |
Chapter 1 Introduction to Machine learning and Supervised Learning -- Chapter 2 Perceptron -- Chapter 3 K-Nearest-Neighbor -- Chapter 4 The Naïve Bayes Method -- Chapter 5 Decision Tree -- Chapter 6 Logistic Regression and Maximum Entropy Model -- Chapter 7 Support Vector Machine -- Chapter 8 Boosting -- Chapter 9 EM Algorithm and Its Extensions -- Chapter 10 Hidden Markov Model -- Chapter 11 Conditional Random Field.
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| 주제 |
Machine learning.
Machine Learning.
Statistical Learning.
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| 보유판 및 특별호 저록 |
Springer Nature eBook
Printed edition: 9789819939169
Printed edition: 9789819939183
Printed edition: 9789819939190
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| QR CODE |
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