Madio.net Mathematics China /// Editor: Yu Dizongxuan This article is reprinted from the Mathematics Algorithm Club The distinction between statistics and machine learning has always been vague.Both in industry and academia, it has been widely believed that machine learning is just a shiny facade over statistics.Moreover, artificial intelligence, supported by machine learning, is also referred … Read more
Click on the top “Visual Learning for Beginners“, select “Star” or “Pin“ Essential content delivered to you first All algorithms in machine learning rely on minimizing or maximizing a certain function, which we call the objective function. The set of functions to be minimized is referred to as the loss function. The loss function measures … 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
Source: Robot Network In fact, artificial intelligence has been a part of our lives for a long time. However, for many people, artificial intelligence is still a relatively “profound” technology,but no matter how profound the technology is, it starts from basic principles.There are 10 major algorithms in the field of artificial intelligence, which are quite … Read more
1. Introduction to Linear Regression 1.1 Origin of Regression Francis Galton, a British biologist, studied the relationship between the heights of parents and their children. He concluded that if parents are taller than the average height of the population, their children tend to be shorter than their parents, moving closer to the average height of … Read more
In last week’s artificial neural network course, we introduced the connection between Support Vector Machines (SVM) and feedforward networks RBF in machine learning, and the representation of adaptive linear elements (ADLINE) composed of linear functions in a single-layer network is quite similar to adaptive filters in traditional signal processing. All of this shows that neural … Read more
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