XGBoost (eXtreme Gradient Boosting) has become quite popular in various competitions in recent years due to its excellent predictive performance. Below, we will introduce its principles. Principle First, we need to understand that XGBoost is an improvement of the GBDT algorithm. During the k-th iteration, the loss function of GBDT can be denoted as L(y,F[k](x)). … Read more
Recently, the research team of the National Key Laboratory of Space-Based Integrated Information System at the Software Institute had their paper Intriguing Property and Counterfactual Explanation of GAN for Remote Sensing Image Generation accepted by the top journal in the field of computer vision, the International Journal of Computer Vision (IJCV). The paper presents a … Read more
Click on the above “Beginner Learning Vision“, select to add “Star” or “Top“ Essential insights delivered promptly Reprinted from: Author | Charlotte Source | Deep Learning Enthusiasts Editor | Jishi Platform Summary of tuning techniques, all about CNN optimization. Summary of CNN Optimization Systematic evaluation of CNN advances on the ImageNet Using ELU non-linearity without … Read more
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