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Video link https://www.bilibili.com/video/BV1Wf4y1Y7uh Qt common tools assistant: api manual qmake: qt builder designer: graphical interface design uic: convert the interface designed by designer into C + + or py file rcc: resource compiler moc: meta object compiler qtcreator: integrated development environment Making the first GUI prog ...

This practical project is based on the dataset of Lending Club [dataset address: https://github.com/H-Freax/lendingclub_analyse/data/ ] This practical project is based on Colab environment brief introduction This practical project of data analysis is divided into two parts. The first part mainly introduces the Baseline method based on Lig ...

Basic concepts of decision tree Decision tree is a tree. The leaf node corresponds to the decision result, and each other node corresponds to an attribute test;The sample set contained in each node is divided into sub nodes according to the results of attribute test;The root node contains the complete set of samples, and the path from the roo ...

catalogue Walk into the decision tree Case 1 Case 2 Tree of soul Selection mechanism of decision tree Measurement rules of node purity Measurement of purity Background introduction of decision tree algorithm Information and quantification of information Information entropy Conditional entropy Information Gain (used by ID3 algorithm) ...

Recently, because of the great innovation, I began to learn machine learning. In the process of learning decision tree, I saw the related operations of decision tree visualization. Firstly, the tree object of sklearn library is used for tree building and model training: from sklearn import tree # Establish decision tree classifier dtc = t ...

preface In the supervised learning algorithm of machine learning, our goal is to learn a stable model with good performance in all aspects, but the actual situation is often not so ideal. Sometimes we can only get multiple preferred models (weak supervised model, which performs better in some aspects). Three cobblers make Zhuge Liang. Ensemble ...

Simple regression prediction of random forest Random forest is a concrete implementation of bagging method. It will train multiple decision trees, and then integrate these results to be the final result. Random forest can be used for splitting or regression. It mainly depends on the selection of decision tree types, and selects specific type ...

summary It is said that this tutorial focuses on application. I haven't understood the principle yet. I read the first six chapters when eating melons. It's also vague..... sklearn is to switch packages. I hope I can learn. The process is: Instantiate and establish the evaluation model object;Train the model through the model interface;Extrac ...

Integrated learning To be exact, ensemble learning is not a real machine learning algorithm, at least it does not introduce any new learning algorithm in essence. The overall idea of ensemble learning is to complete the final task through multiple basic (weak) learners. Just as it used to be a single challenge between an algorithm and a proble ...

Tip: here is a hard Ken 📕 If Xiaobai makes a mistake, change it. Don't spray it:) preface The sky can be mended, the sea can be filled, the mountains can be moved, the sun and the moon are past, and can not be pursued again. Decision Tree is based on tree structure to make decisions. (classification, regression) A decision tree contai ...