- ML Introduction
- ML Logistic Regression
- ML Linear Regression
- ML Data Clustering
- ML Categorical Data
- ML Decision Tree
- ML K-Means
- ML KNN
- ML Linear Graph
- ML Data Cleaning
- ML Data Distribution
- ML Standard Deviation
- ML Scatter Plot
- ML Polynomial Regression
- ML Confusion Matrix
- ML K Nearest Neighbor
- ML Training
- ML Data Distribution
- ML Classification Regression
- ML Random Forest
- ML Deployment
- ML Deep Learning
- ML Reinforcement Learning
- ML Dimensionality Reduction
- ML Neural Network
ML K Nearest Neighbor.
The k-nearest neighbors (KNN) algorithm is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point. It is one of the popular and simplest classification and regression classifiers used in machine learning today.