(Click the public account above to quickly follow) Source: Qiu Kang singasong https://segmentfault.com/a/1190000006070219 Introduction I previously developed a campus dating APP, where one of the logics was to confirm that the user is a student by accessing their academic system. The basic idea was to use the user’s account and password to scrape the information. … Read more
Improving kNN Matching Effect for Dating Websites This article follows up on the previous one, in which we briefly introduced the basic principles of the kNN algorithm. Using the context of dating website matching, we implemented data parsing from a text file using Python and created scatter plots with matplotlib for data analysis. In this … Read more
CodingGo Technical Community A Free Programming Learning Platform Algorithm Introduction KNN (K-Nearest Neighbors) is a simple machine learning algorithm that does not require learning any parameters and can be used for both classification and regression problems. The intuitive explanation of this algorithm is ‘Birds of a feather flock together.’ When a new sample is input, … Read more
This article is an outstanding article from the Kexue Forum, Author ID: 大大薇薇 1 Overview python_mmdt: A Python library that generates feature vectors based on sensitive hashing (Part 1)We introduce a method called mmdthash (sensitive hashing) and provide a basic introduction to its concepts. python_mmdt: From 0 to 1 – Implementing a Simple Malicious Code … Read more
Produced by | Yan Zhi Knowledge Circle | To join the “Domain Controller Group,” please add WeChat 136581676, note domain Machine learning is familiar to everyone; it is a branch of artificial intelligence (AI) and computer science that mainly uses data and algorithms to mimic human learning processes, gradually improving its accuracy. The rapid development … Read more
K-nearest neighbor (KNN) is one of the most popular algorithms in machine learning, widely used in both supervised and unsupervised learning. In supervised learning, KNN is used to calculate the distance to k neighbors and can define outliers. In unsupervised learning, KNN is also used to calculate the distances to neighbors and then define outliers. … Read more
Python Tribe (python.freelycode.com) organized the translation, welcome to forward, prohibited from reprinting The k-Nearest Neighbors algorithm (KNN) is based on a simple logic that is easy to understand and implement, making it a powerful tool you can use. By learning this tutorial, you will be able to implement a KNN algorithm from scratch in Python. … Read more
This series of tutorials serves as notes for the book “Hands-On Machine Learning.” First, let’s discuss the reasons for writing this series: First, the code in “Hands-On Machine Learning” is written in Python 2, and some of the code will throw errors when run on Python 3. This tutorial revises the code based on Python … 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
KNN Practical Application – Improving Matchmaking Effectiveness Introduction In simple terms, the KNN algorithm classifies data by measuring the distances between different feature values. The working principle is that there exists a sample dataset, namely the training dataset, and each sample in the dataset has a label, which indicates the correspondence between each data point … Read more