Full Link: https://tecdat.cn/?p=34635 Analyst: Lingzi Lu Customer churn is a serious problem that exists in various industries, and it has also attracted the attention of numerous telecom service providers—because the cost of acquiring a new customer far exceeds the cost of retaining an existing customer（Click “Read the Original” at the end for complete data）。 Related … Read more
I previously wrote two articles on address processing, detailed below: Address Processing in Risk Control: Simple and Effective Regex Replacement Address Processing in Risk Control: Simple, Accurate, and Effective Multi-label Clustering Today we are writing the third article, using KNN to construct similar addresses. Although this article is about addresses, many scenarios can draw on … Read more
Anyone involved in econometrics should follow this account. Manuscript:[email protected] All econometrics methodologiesCode programsMacro and microdatabases and various softwareare all shared in the community. Welcome to exchange and visit the econometrics circle community. Regarding machine learning methods, refer to the following articles:1Machine learning methods have appeared in top journals such as AER, JPE, QJE!, 2Frontier: A … Read more
This article is reprinted from the public account Xinkou Dushuo KNN is a fundamental data classification algorithm in machine learning. Here, I will explain its utility through a story. Let’s start with a joke. During a matchmaking event, a beautiful girl asked the young man: Do you have a three-bedroom apartment? The young man: No. … Read more
K-Nearest Neighbors (KNN) The K-Nearest Neighbors (KNN) model is a simple and effective machine learning algorithm mainly used for classification and regression tasks. The basic idea of KNN is that the class or value of a sample depends on the classes or values of its k nearest neighbors. Specifically, KNN predicts the class or value … 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
(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
KNN (K-Nearest Neighbors) algorithm is a simple yet effective classification and regression algorithm. Its basic idea is to classify or predict by calculating the distance between samples. Below is an example of KNN algorithm implementation in Python, including data preparation, model training, and prediction. 1. Install Required Libraries If you haven’t installed scikit-learn and numpy, … Read more
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
Ultrasonic transducers have been widely used in object detection, non-destructive testing (NDT), biomedical imaging, and therapy. Compared to bulk ultrasonic transducers, piezoelectric micromachined ultrasonic transducers (PMUTs) with a small footprint have advantages such as low power consumption and wide bandwidth, making them suitable for various applications in consumer electronics and the Internet of Things (IoT), … Read more