Preface ROC (Receiver Operating Characteristic) curve and AUC are often used to evaluate the quality of a binary classifier. This article will first briefly introduce ROC and AUC, and then use examples to demonstrate how to make ROC curves and calculate AUC in python. Introduction to AUC AUC (Area Under Curve) is a very commonly used evaluation index in machine learning binary classification models. Compared with F1-Score, it has greater tolerance for project imbalance. Currently, it is commonly used in machine learning libraries (such as scikit- learn) generally integrates the calculation of this indicator, but sometimes the model is separate or written by itself. At this time, if you want to evaluate the quality of the training model, you have to build an AUC calculation module yourself. This article found libsvm when querying the information. -tools has a very easy-to-understand auc calculation, so I picked it out for future use. AUC calculation The calculation of AUC is divided into the following three steps: 1. Preparation of calculation data, if only
1 is used during model training. Python draws ROC curve and calculates AUC value
Introduction: This article introduces how to use Python to draw ROC curves and calculate AUC values, if necessary Friends can refer to it, let’s take a look below.
2. There is a question about the sql left connection. Why are all nulls found instead of no data?
Introduction: domain is the domain name table, domain_sell is the listed domain name table, domain_auction_history is the domain name auction table. This is my query statement: SELECT d. ,s.,MAX(h.price) AS max_price FROM domain d LEFT JOIN domain_sell s USING(domain_id) LEFT JO...
3. Build PHP on GAE Environment and enable URL rewriting gae tutorial gae website gaebol
Introduction: gae, php: Set up a PHP environment on GAE and enable URL rewriting: 1. Download quercus:http Of course, the latest version of ://quercus.caucho.com/ is the best, because in principle, the new version supports PHP better. However, during my own testing, I found that the latest 4.0.25 had some problems, so I switched to 4.0. Version 18. Select the WAR format file to download, use Winrar to decompress it, and copy the WEB-INFlib jar to the warWEB-INFlib directory under the GAE project 2. Configure Quercus: in appendin
##4 . floccinaucinihilipilification Linux The solution to the problem that the array element obtained by fgetcsv is an empty string
Introduction: floccinaucinihilipilification:floccinaucinihilipilification The solution to the problem that the array element obtained by Linux fgetcsv is an empty string Method: But on the server, many Linux servers are used, and the source program uses UTF-8, which can easily cause character encoding problems. If you just transcode the CSV file to UTF-8, there will be no problem on the Windows server, but on RedHat5 .5, in the array obtained with fgetcsv, if the content of a column is Chinese, the array element corresponding to the column is an empty string, while English is normal. At this time, you need to set the area:
5. Discuss the use analysis of Hessian in PHP_PHP tutorial
Introduction: Discuss the use analysis of Hessian in PHP. What is Hessian? Hessian is an open source remote communication protocol provided by caucho. It adopts binary RPC protocol and is based on HTTP transmission. There is no need to open another firewall port on the server side. Protocol
6. Build a PHP environment on GAE and enable URL rewriting_PHP tutorial
Introduction: Set up a PHP environment on GAE and enable URL rewriting. 1. Download quercus: http://quercus.caucho.com/ Of course, the latest version is the best, because in principle, the new version supports PHP better, but when I tested it, I found that the latest 4.0.25 exists
7. Using PHP as a Spring MVC View via Quercus (transfer)_PHP tutorial
Introduction: Using PHP as a Spring MVC View via Quercus (transfer). Original post: http://blog.caucho.com/2009/04/14/using-php-as-a-spring-mvc-view-via-quercus/ This week, Ive been prepping for a talk on Quercus in which I promised to show a demo of Spr
8. Flying Saucer implements html to pdf (some problems, continuous updates)_html/css_WEB-ITnose
Introduction: Flying Saucer implements html to pdf (some issues, continuously updated)
##9. (Oralce) Web page turning optimization example
Introduction: (Oralce) Web page turning optimization example web|page turning|optimization
10. Mysql database learning experience (4)
Introduction: Mysql database learning experience (4)
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Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


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