1. Overview of KNN Algorithm KNN can be said to be one of the simplest classification algorithms, and it is also one of the most commonly used classification algorithms. Note that KNN is a supervised learning classification algorithm, which looks somewhat similar to another machine learning algorithm, Kmeans (Kmeans is an unsupervised learning algorithm), but … 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
The KNN algorithm is one of the most basic instance-based learning methods. First, we will introduce the relevant concepts of instance-based learning. 1. Instance-Based Learning 1. Given a series of training samples, many learning methods establish a clear generalization description for the objective function; however, instance-based learning methods simply store the training samples. The work … Read more
Click on the above “Beginner’s Guide to Vision“, select to add “Star” or “Pin“ Essential insights delivered promptly Introduction The idea of KNN (k-Nearest Neighbors) is simple, and the mathematical knowledge required is almost zero, making it very practical as an introduction to machine learning. It can explain many details during the use of machine … Read more
1. Logistic Regression The binary logistic regression model is a classification model represented by the conditional probability distributionP(Y|X), with 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 method. … Read more
Original: Medium Author: Shiyu Mou Source: Robot Circle This article has a length of 4600 words and is suggested to be read in 6 minutes. This article introduces you to 5 techniques for image classification, summarizes and consolidates algorithms, implementation methods, and conducts experimental validation. The image classification problem is the task of assigning labels … Read more
As students entering the field of machine learning, many commonly used algorithms might not be very familiar to you. No worries! This article will definitely provide you with a complete overview~ Like and save it for slow learning~ Basic Machine Learning Algorithms: ·Linear Regression ·Support Vector Machine ·K-Nearest Neighbors ·Logistic Regression ·Decision Tree ·K-Means ·Random … Read more
A public academic platform initiated by overseas scholars Sharing information, integrating resources Exchanging academics, occasionally discussing literature High-performance piezoelectric ceramics are a crucial type of material in modern electronic devices. In pursuit of sustainable development, traditional lead-based piezoelectric materials dominated by PbZr1−xTixO3 (d33 ≈ 200-1500 pC/N) are gradually transitioning to lead-free piezoelectric ceramics based on … Read more
Recently, interesting works in the AIGC community have emerged one after another, thanks to the success of Diffusion Models. As an emerging topic in generative AI models, diffusion models have brought us many surprises. However, it is important to note that current text-to-image diffusion models require large-scale text-image paired datasets for pre-training, making it very … Read more