XGBoost has shone in Kaggle competitions. In previous articles, the principles of the XGBoost algorithm and the XGBoost splitting algorithm were introduced. Most explanations of XGBoost parameters found online only scratch the surface, making it extremely unfriendly for those new to machine learning algorithms. This article will explain some important parameters while referencing mathematical formulas … Read more
In the process of developing machine learning models, evaluating the performance of a model is a crucial step. Through evaluation, we can understand the model’s generalization ability, that is, its performance on unseen data. Cross-validation and test sets are two commonly used evaluation methods, each with its specific use cases and advantages. This article will … Read more
Honestly, every time I write machine learning code with Scikit-learn, I feel an inexplicable thrill. This library is like our helpful assistant, wrapping complex machine learning algorithms in a simple and easy-to-use way, allowing us to focus on solving real problems rather than getting bogged down in the details of algorithm implementation. Installation and Import … Read more