Simple and crude understanding and implementation of machine learning ensemble learning (III): Boosting the principle of integration, implementation, api introduction, GBDT, XGBoost, Taylor expansion - Code World

Simple and crude understanding and implementation of machine learning ensemble learning (III): Boosting the principle of integration, implementation, api introduction, GBDT, XGBoost, Taylor expansion

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Origin blog.csdn.net/qq_35456045/article/details/104644962

Simple and crude understanding and implementation of machine learning ensemble learning (III): Boosting the principle of integration, implementation, api introduction, GBDT, XGBoost, Taylor expansion

Integrated learning, Bagging integration principle, random forest construction process, random forest api and cases, boosting integration principle, gradient boosting decision tree (GBDT), XGBoost and Taylor expansion

Simple and crude understanding and implementation of integrated machine learning Learning (II): Bagging integration principle, random forest construction process, random forest api reports, random forest predict cases, bagging integration advantages

Simple and crude understanding and implementation of machine learning integrated learning (a): Introduction to integrated learning algorithms, machine learning two core tasks, integrated learning and boosting Bagging

Simple and crude understanding and implementation of machine learning clustering algorithm (III): clustering algorithm implementation process, k-means clustering step, case

Simple and crude understanding and implementation of machine learning linear regression (two): Preliminary using linear regression api, Case

Simple and crude understanding and implementation of machine learning clustering algorithm (B): clustering algorithm api initial use case

Simple and crude understanding and implementation of machine learning linear regression (III): mathematics: the derivative guide, common functions, derivative of four operations, matrix (vector) derivative

Simple and crude understanding and implementation of machine learning clustering algorithm (VIII): machine learning algorithm selection guide

Simple and crude understanding and implementation of machine learning linear regression (XI): save and load API sklearn model, the model of linear regression saving load case

Machine Learning - Integrated Learning (boosting, bagging, Adaboos, GBDT, XGBoost)

Simple and crude understanding and implementation of machine learning linear regression (VII): Boston house prices forecast

Simple and crude understanding and implementation of machine learning linear regression (six): Linear regression api re-introduced --sklearn.linear_model.LinearRegression (fit_intercept = True)

Simple and crude understanding and implementation of machine learning linear regression (X): Improved linear regression - ridge regression, Boston prices forecast

Simple and crude understanding and implementation of machine learning linear regression (a): Linear regression analysis of the relationship between profiles, application scenarios, features and objectives

Simple and crude understanding and implementation of machine learning clustering algorithm (VII): clustering Case: Explore user preferences for goods categories subdivided dimensionality reduction

Simple and crude understanding and implementation of machine learning linear regression (VIII): underfitting and over-fitting causes and solutions, regularization, dimensional disaster

Simple and crude understanding and implementation of machine learning clustering algorithm (VI): [feature] project - feature reduction, feature selection, principal component analysis (PCA), Case

Machine Learning: GBDT (Gradient Boosting Decision Tree)

"Machine Learning Formula Derivation and Code Implementation" chapter11-GBDT

[Machine Learning Algorithm] 3. Integration algorithm: RF, AdaBoost, GBDT, XGBoost, LightGBM, Stacking model fusion

[Machine Learning] knn (principle analysis + code implementation)

Express implementation principle learning - simple simulation

[Machine Learning] Detailed Interpretation of XGBoost (Integrated Learning_Boosting_GBM)

[Machine Learning Core Summary] What is GBDT (Gradient Boosting Tree)

Simple and crude understanding and implementation of machine learning neural network NN (IV): word vector -word2vec, Word2Vec model introduction, statistical language model, neural network model language NNLMNNLM, Word2Vec case Word2vec, word vector tools

The Road to Machine Learning: Python Practical Boosting Tree XGBoost Classifier

Integrated Learning - Boosting Algorithm: Brief Principles and Differences of Adaboost, GBDT, XGBOOST and lightGBM

Introduction to machine learning, ALS, LR, GBDT [reproduced]

[Machine Learning] Boosting method AdaBoost two-classification example C++ implementation

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