Click on the above “Beginner Learning Vision”, choose to add “Star” or “Top” Heavyweight content delivered first-hand We train and learn the models well, and only through objectively evaluating the model’s performance can we make better practical decisions. Model evaluation mainly includes: prediction error situations, degree of fitting, model stability, etc. There are also some … Read more
Author: AISHWARYA SINGH, AUGUST 22, 2018 Translator: ZHAO XUEYAO Proofreader: ZHANG LING This article is approximately 4200 words, and is recommended for a 10 minute read. This article explains the basic working principle of the K-Nearest Neighbors (KNN) algorithm and briefly introduces three methods for calculating the distance between points. Introduction Among all the machine … Read more
1 Introduction Our lives are always filled with various small choices. Although these choices may not have a significant impact on us, they can still cause some frustration. For example, what to eat for lunch, where to travel during the holidays, etc. How do you usually solve such problems? If you were to choose a … Read more
1. Basic Concepts The K-nearest neighbors method (KNN) can be used for both classification and regression. The difference between KNN for regression and classification lies in the decision-making process during the final prediction. When KNN is used for classification, it generally employs a majority voting method. When KNN is used for regression, it typically uses … Read more
Source: DeepHub IMBA This article is about 1700 words, and it is recommended to read for 7minutes. This article compares KNN with simple linear regression. Generally, k-Nearest Neighbor (KNN) is used to solve classification problems; in fact, KNN is a simple algorithm that can be applied to both data classification and prediction. In this article, … Read more
Machine learning is a hot topic, but apart from the teachers who know it well, very few people can explain what it’s all about. If you read articles about machine learning online, you’re likely to encounter one of two situations: either a heavy academic trilogy filled with various theorems (I struggle to grasp even half … Read more
Machine learning is divided into two main categories based on model types: supervised learning models and unsupervised learning models. 1. Supervised Learning Supervised learning typically uses training data with expert-labeled tags to learn a function mapping from input variable X to output variable Y. Y = f(X), where training data is usually in the form … Read more
Source: dataxon Translator: Ahong Everyone is talking about machine learning, but very few people can explain what it really is, apart from the teachers who know it inside out. If you read articles about machine learning online, you are likely to encounter two scenarios: heavy academic tracts filled with various theorems (I struggle to grasp … Read more
Source: Author: james_aka_yale Hello everyone, I am Xiao Z. In the field of machine learning, there is a saying that “there is no free lunch in the world”, which simply means that there is no single algorithm that performs best on every problem. This theory is particularly important in supervised learning. For example, you cannot … Read more
Machine learning is a hot topic, but aside from the experts, very few people can explain it clearly. If you read articles about machine learning online, you are likely to encounter two situations: heavy academic works filled with various theorems (I can barely handle half a theorem), or dazzling stories about artificial intelligence, data science … Read more