Lecture Notes on Support Vector Machine Feng Li fli@sdu.edu.cn Shandong University, China 1 Hyperplane and Margin In a n-dimensional space, a hyper plane is defined by ωT x + b = 0 (1) where ω ∈ Rn the margin is defined as γ = min i γ(i) (6) 1 ? ? ! ? ! Figure 1: Margin and hyperplane. 2 Support Vector Machine 2.1 Formulation The hyperplane actually serves as a decision boundary to differentiating samples are so-called support vector, i.e., the vectors “supporting” the margin boundaries. We can redefine ω by w = � s∈S αsy(s)x(s) where S denotes the set of the indices of the support vectors 4 Kernel

Lecture 6: Support Vector Machine Feng Li Shandong University fli@sdu.edu.cn December 28, 2021 Feng Li (SDU) SVM December 28, 2021 1 / 82 Outline 1 SVM: A Primal Form 2 Convex Optimization Review parallely along ω (b < 0 means in opposite direction) Feng Li (SDU) SVM December 28, 2021 3 / 82 Support Vector Machine A hyperplane based linear classifier defined by ω and b Prediction rule: y = sign(ωTx Scaling ! and " such that min& ' & !() & + " = 1 Feng Li (SDU) SVM December 28, 2021 14 / 82 Support Vector Machine (Primal Form) Maximizing 1/∥ω∥ is equivalent to minimizing ∥ω∥2 = ωTω min ω,b ωTω

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contrib/gunicorn.py docker_registry.wsgi:application 或者 $ sudo gunicorn --access-logfile - --error-logfile - -k gevent -b 0.0.0.0:5000 -w 4 --max-requests 100 docker_registry.wsgi:application 此时使用 curl 访问本地的

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use single threshold, set pd.options.display.min_rows = None. 1.1.5 Json normalize with max_level param support json_normalize() normalizes the provided input dict to all nested levels. The new max_level parameter keywords logy, logx and loglog can now accept the value 'sym' for symlog scaling. (GH24867) • Added support for ISO week year format (‘%G-%V-%u’) when parsing datetimes using to_datetime() (GH16607) • Indexing

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use working with strings. See Text Data Types for more. 1.3.3 Boolean data type with missing values support We’ve added BooleanDtype / BooleanArray, an extension type dedicated to boolean data that can hold encourage use of the extension dtypes StringDtype, BooleanDtype, Int64Dtype, Int32Dtype, etc., that support pd.NA, the methods DataFrame.convert_dtypes() and Series.convert_dtypes() have been introduced. (GH29752)

Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use single threshold, set pd.options.display.min_rows = None. 1.1.5 Json normalize with max_level param support json_normalize() normalizes the provided input dict to all nested levels. The new max_level parameter keywords logy, logx and loglog can now accept the value 'sym' for symlog scaling. (GH24867) • Added support for ISO week year format (‘%G-%V-%u’) when parsing datetimes using to_datetime() (GH16607) • Indexing

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2478 4.7.2 Python support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2479 4.8 Roadmap Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use tables of data. To introduction tutorial To user guide Straight to tutorial... pandas has great support for time series and has an extensive set of tools for working with dates, times, and time- indexed

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2478 4.7.2 Python support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2479 4.8 Roadmap Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use tables of data. To introduction tutorial To user guide Straight to tutorial... pandas has great support for time series and has an extensive set of tools for working with dates, times, and time- indexed

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2384 4.7.2 Python Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2385 4.8 Roadmap Version | Zipped HTML Useful links: Binary Installers | Source Repository | Issues & Ideas | Q&A Support | Mailing List pandas is an open source, BSD-licensed library providing high-performance, easy-to-use tables of data. To introduction tutorial To user guide Straight to tutorial... Pandas has great support for time series and has an extensive set of tools for working with dates, times, and time- indexed