What is the K-Nearest Neighbors Algorithm (KNN)? The K-Nearest Neighbors algorithm (KNN) is a simple and intuitive machine learning algorithm widely used for classification and regression tasks. Its core idea is based on the principle of “birds of a feather flock together,” finding the K most similar neighbors by comparing the distance between a new … Read more
Hello everyone, I am Xiaohan. Today, I will share a powerful algorithm model, KNN. KNN (K-Nearest Neighbors) is an instance-based supervised learning algorithm widely used in classification and regression tasks. Its core idea is: given a sample, calculate its distance to all samples in the training set, find the K nearest samples (the nearest neighbors), … Read more
Full Article Link: https://tecdat.cn/?p=33917 KNN is a non-parametric learning algorithm, which means it makes no assumptions about the underlying data. This is a very useful feature because most client data does not really follow any theoretical assumptions, such as linear separability, uniform distribution, etc. (Click the “Read the Original” link at the end of the … Read more
Today is the seventh issue summarizing 16 major topics and 124 interview questions in machine learning: K-Nearest Neighbors (KNN) algorithm interview questions. The K-Nearest Neighbors (KNN) algorithm works by finding the K nearest neighbors of a sample and using the information from these K neighbors to make predictions. For classification tasks, the majority voting method … Read more
Hello everyone, today let’s talk about XGBoost~ XGBoost (Extreme Gradient Boosting) is particularly suitable for variants of Gradient Boosting Decision Trees. It was proposed by Tianqi Chen in 2016 and has been widely popular in machine learning competitions such as Kaggle. The historical background of XGBoost can be traced back to the Gradient Boosting algorithm, … Read more
Source fromMedium Author: garvitanand2 Compiled by: Machine Heart Contributors: Geek AI, Lu This article introduces the 10 most commonly used machine learning algorithms, including linear regression, Logistic regression, linear discriminant analysis, Naive Bayes, KNN, random forest, etc. 1. Linear Regression In the fields of statistics and machine learning, linear regression may be one of the … Read more
How to Obtain 1. Follow the public account below, and click 【Like】 and 【View】 in this article 2. Click 【Get Course】 in the public account to obtain this material There is a course on Basics of Machine Learning: Machine Learning and Materials/Chemistry Basics of Machine Learning: Machine Learning and Materials/Chemistry 1. Introduction to Machine Learning … Read more
Generally, BCO provides a good option for maximizing oil production in brownfields, allowing access to remaining oil targets after existing completions. Proper BCO maturity, including small reservoir unit analysis, can yield high returns and low-risk projects to acquire cheap oil at low cost. Unfortunately, the lack of appropriate resources, such as potential manpower and budget … Read more
Produced by Big Data Digest Compiled by: Hong Yingfei, Ning Jing PyTorch, one of the deep learning framework libraries, is an open-source deep learning platform from Facebook that provides seamless transition from research prototypes to production deployment. This article aims to introduce the basics of PyTorch, helping beginners write initial Python PyTorch code in 4 … Read more