Table of Contents 1. Principles of KNN Algorithm 2. Three Elements of KNN Algorithm 3. Brute Force Implementation of KNN Algorithm 4. KD-Tree Implementation of KNN Algorithm 5. Imbalance in Training Samples for KNN Algorithm 6. Advantages and Disadvantages of the Algorithm 1. Principles of KNN Algorithm The KNN algorithm selects the k nearest training … Read more
Produced by | Yan Zhi Knowledge Circle | To join the “Domain Controller Group,” please add WeChat 136581676, note domain Machine learning is familiar to everyone; it is a branch of artificial intelligence (AI) and computer science that mainly uses data and algorithms to mimic human learning processes, gradually improving its accuracy. The rapid development … Read more
Python Tribe (python.freelycode.com) organized the translation, welcome to forward, prohibited from reprinting The k-Nearest Neighbors algorithm (KNN) is based on a simple logic that is easy to understand and implement, making it a powerful tool you can use. By learning this tutorial, you will be able to implement a KNN algorithm from scratch in Python. … Read more
XGBoost is well-known as a powerful tool in data science competitions and is widely used in the industry. This article shares a collection of frequently asked interview questions about XGBoost that I have compiled over the years, hoping to deepen everyone’s understanding of XGBoost and, more importantly, to provide some assistance when seeking opportunities. 1. … Read more
Click the top to follow us! XGBoost Feature Engineering: From Beginner to Expert Recently, I’ve been diving into XGBoost and found that feature engineering is indeed a profound subject. This thing can be said to be the lifeline of model performance; if done poorly, all efforts can be in vain. Today, let’s chat about the … Read more
Hello everyone! Niu Ge is back! Today we are going to talk about a very powerful machine learning library – XGBoost. When it comes to it, we must mention its dominance in major data competitions. It’s like the “timely rain Song Jiang” in the machine learning world, always able to help you improve model performance … Read more
Original | ETF Trading Strategy Combining Price Momentum and Crowding Source | China Galaxy Securities Research Institute, Typesetting: Python Data Science 1. Introduction This article mainly introduces the trading strategy for margin-financed ETFs. As an index tracking tool, ETFs have good asset allocation value. At the same time, by combining price diffusion and Minsky moments, … Read more
Selected from Ancestry Author: Tyler Folkman Translated by Machine Heart Contributors: Liu Xiaokun, Li Zenan The algorithm using XGBoost often achieves good results in Kaggle and other data science competitions, making it popular (see: Why Does XGBoost Perform So Well in Machine Learning Competitions?). This article analyzes the prediction process of the XGBoost machine learning … Read more
XGBoost: A Powerful Python Library for Extreme Gradient Boosting Li: Wang, I often feel that my efficiency in data processing and predictive modeling is not high. Is there a good Python library that can help me? 😟 Wang: Of course! 🙌 Today, I will introduce you to XGBoost, which is a great assistant in the … Read more
Core Points:Complete Summary of XGBoost Core Issues! Hello, I am Cos Dazhuang! Today I will share content about XGBoost~ XGBoost is very important, especially excelling in classification, regression, and ranking problems. Its practical applications include financial risk control, medical diagnosis, industrial manufacturing, and advertising click-through rate prediction. With its efficient performance and robustness, XGBoost has … Read more