Source: Not Just Data Analysis This article is about 5800 words long, and it is recommended to read for over 10 minutes. Without statistics, machine learning cannot exist, but due to the contemporary information explosion and the vast amount of data humans can access, machine learning is extremely useful. The distinction between statistics and machine … Read more
The current competition for publishing in bioinformatics is intense, and achieving high scores is challenging! If you rely on conventional methods such as functional enrichment analysis and prognostic model evaluation, you will either pass with low scores, get rejected, or be asked to supplement your experiments… Combining with machine learning makes a difference; machine learning … Read more
Both linear models and decision trees are important types of machine learning.We have spent a lot of time learning linear regression; do you feel like you have opened the door to machine learning?Next, we continue to explore machine learning, from understanding to application. 1. The Role of Prediction and Classification in Machine Learning The purpose … Read more
Author Introduction Zhou Weihua，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Zhai Xiaofeng，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Tan Haowei，Institute of Digital Finance, Chinese Academy of Fiscal Sciences Research on Financial Fraud Prediction Model of Listed Companies Based on XGBoost Research Background In recent years, the Central Committee of the Communist … Read more
In 2020, the “butterfly effect” was triggered in China’s pharmaceutical industry, with the two wings of this butterfly being the introduction of the MAH system and the initiation of centralized procurement. The MAH system is of great significance in encouraging drug innovation and improving drug quality. According to the MAH system, the drug marketing authorization … Read more
With the continuous development of genetics, breeding, and the increasing advancements in the Human Genome Project and molecular biology, biological data has experienced explosive growth over just a few decades. For example, algorithms such as regression analysis, random forests, and support vector machines in bioinformatics are already quite mature. Recently, while reading literature, I came … Read more
1 Algorithm Introduction XGBoost, short for eXtreme Gradient Boosting, is an ensemble learning algorithm based on Gradient Boosting Decision Trees (GBDT). It improves upon GBDT by introducing regularization terms and second-order derivative information, enhancing model performance and generalization ability. As an efficient ensemble learning algorithm, XGBoost effectively utilizes multi-core processors for parallel computing, accelerating the … Read more
Reprinted from:Author: james_aka_yale In the field of machine learning, there is a saying: “There is no free lunch in the world,” which means that no single algorithm can perform best on every problem. This theory is particularly important in supervised learning. For example, you cannot say that neural networks are always better than decision trees, … 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