Hello, I am Xiao Chu~ Today we are going to talk about a topic: using LSTM and KNN for multivariate data anomaly detection. Related Principles Multivariate Data Anomaly Detection is a very important task, especially in complex contexts such as high-dimensional data and time series data. Traditional anomaly detection methods (such as those based on … 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
Authorized Reprint by Author Author: Li Wenzhe Excerpt from: Inclusive Big Data Center Introduction The Knowledge Graph is currently a hot research topic. Since Google launched its first version of the Knowledge Graph in 2012, it has sparked a wave of interest in both academia and industry. Major internet companies quickly launched their own Knowledge … Read more
In recent years, Generative Adversarial Networks (GAN) have rapidly developed and become one of the main research directions in the field of machine learning. GAN is based on the idea of zero-sum games, where its generator and discriminator learn in opposition to capture the data distribution of given samples, generating new sample data. A large … Read more