Click the “Datawhalee” above and select “star” in the official account Get valuable content instantly This is the third article on decision trees, mainly introducing mainstream ensemble algorithms based on the Boosting framework, including XGBoost and LightGBM. Here is the complete mind map: XGBoost XGBoost is a tool for large-scale parallel boosting trees. It is … Read more
XGBoost is the most famous algorithm for handling different types of tabular data, with LightGBM and Catboost released to address its shortcomings. On September 12, XGBoost released the new version 2.0. This article will not only introduce the complete history of XGBoost but also discuss the new mechanisms and updates. This is a long article, … Read more
Machine learning is essentially a search in space and generalization of functions. Now enterprises mainly rely on supervised learning based on samples. In reality, logistic regression (LogisticRegression, LR) has a fast training speed and strong interpretability, but its fitting accuracy is insufficient. On the other hand, support vector machines (SupportVectorMachine, SVM) have high prediction accuracy, … Read more
Source: AI Technology Review, DataPi THU This article is about 7100 words long and is recommended for a 13-minute read. It summarizes the historical origins of several foundational algorithms in the field of machine learning. Recently, Andrew Ng updated a blog post on his founded AI Weekly, “The Batch”, summarizing the historical origins of several … Read more
1. Logistic Regression The binary logistic regression model is a classification model represented by the conditional probability distribution P(Y|X), in the form of a parameterized logistic distribution. Here, the random variable X takes real values, and the random variable Y takes values of 1 or 0. The model parameters can be estimated using a supervised … Read more
1. Linear Regression Linear regression is a statistical method used to study the relationship between two continuous variables: one independent variable and one dependent variable. The goal of linear regression is to find the best-fit line through a set of data points, which can then be used to predict future observations. The equation for a … Read more
Click on the above“Beginner Learning Vision” to select “Star” or “Pin” Important content delivered at the first time Linear Models Linear models are the simplest and most basic machine learning models. Their mathematical form is as follows: g(x;w)=. Sometimes, we also add a bias term b on top of, but as long as we expand … Read more
This session shares as the title: What Exactly Is Machine Learning A Beginner’s Tutorial to Understand Machine Learning //// //// First Steps in Machine Learning Of course, it’s to understand its basic concepts This article summarizes insights from the internet, personal learning notes✍ What is machine learning, and why does it have such great power? … Read more
Source: Zhihu Abner says AI This article is approximately 4500 words long and suggests a reading time of 9 minutes. This article summarizes the pros and cons of the top 10 machine learning algorithms. 1. Logistic Regression The binary logistic regression model is a classification model represented by the conditional probability distributionP(Y|X), which takes the … Read more
The Gradient Boosting Decision Tree (GBDT), as a leader in ensemble learning, has won the favor of many data scientists due to its excellent performance in classification and regression tasks. This article will take you deep into the mysterious veil of GBDT and demonstrate how to efficiently implement GBDT using the sklearn library. 1. What … Read more