▍1. Python_2
This is a guide book how to code with python
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▍2. backend
This example demonstrates how to use the backend service in Google-App-Engine. 1. Change name of application in app.yml and firstmodule.yaml to the name of you application 2. Upload the files 3. Open the main page
▍3. readfile
This example demonstrates how to read a raw file in Google-App-Engine. 1. Change name of application in app.yml to the name of you application 2. Upload the files 3. Open the main page
▍5. adaboost
AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。 具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后， 计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法....... 直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。 可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。 AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。 对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目， 过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。 同时可以通过删除离决策边界比较远的样例。 (AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative. Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way ....... 0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value). As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing. AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method. For )
▍6. centrality
计算复杂网络中的节点或边的介数中心性，基于python的复杂网络工具箱(Betweenness centrality computational complexity of the network nodes or edges, based on a complex network toolbox python)
▍7. A-Learners-Guide-to-Programming-Using-the-Python-
A Learner s guide for programming using python language.
▍8. object-intersection
blender script to make a object intersection
▍9. object-intersection
blender script to make a object intersection
▍10. CARO-System-Specification---Pham-Cao-Nhat-Phuong-
Caro game system specification Netcetric
▍11. CARO-System-Specification---Pham-Cao-Nhat-Phuong-
Caro game system specification Netcetric
▍12. arithmetic2
Data Compression Arthmetic Algorithm Example. Tested in Python 2.7 just run py file
▍13. arithmetic2
Data Compression Arthmetic Algorithm Example. Tested in Python 2.7 just run py file
▍14. huffman_alphabet
Data Compression Huffman Coding Example Create an huffman alphabet for the input string Python 2.7 necessary (not tested Python 3.0). For windows just run huffman.bat
▍15. huffman_alphabet
Data Compression Huffman Coding Example Create an huffman alphabet for the input string Python 2.7 necessary (not tested Python 3.0). For windows just run huffman.bat
▍16. l2_bayes_classifier
machine learning 方面有关于The Bayes Classifier的资料，语言是python(machine learning aspects have The Bayes Classifier information about language is python)
▍17. l2_bayes_classifier
machine learning 方面有关于The Bayes Classifier的资料，语言是python(machine learning aspects have The Bayes Classifier information about language is python)
▍18. w7_gaussianProcesses
machine learning 方面有关于Bayesian Review and Gaussian Processes的资料，语言是python(machine learning aspects of information concerning the Bayesian Review and Gaussian Processes, language is python)
▍19. w7_gaussianProcesses
machine learning 方面有关于Bayesian Review and Gaussian Processes的资料，语言是python(machine learning aspects of information concerning the Bayesian Review and Gaussian Processes, language is python)
▍20. w5_bayesianRegression
machine learning 方面有关于Bayesian Regression的资料，语言是python(There are aspects of machine learning Bayesian Regression information about language is python)
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