K Nearest Neighbor Classifier, Explained: A Visual Guide with Code Examples for Beginners
CLASSIFICATION ALGORITHM
⛳️ More CLASSIFICATION ALGORITHM, explained: · [Dummy Classifier](https://towardsdatascience.com/dummy-classifier-explained-a-visual-guide-with-code-examples-for-beginners-009ff95fc86e) ▶ [K Nearest Neighbor Classifier](https://towardsdatascience.com/k-nearest-neighbor-classifier-explained-a-visual-guide-with-code-examples-for-beginners-a3d85cad00e1) · [Bernoulli Naive Bayes](https://towardsdatascience.com/bernoulli-naive-bayes-explained-a-visual-guide-with-code-examples-for-beginners-aec39771ddd6) · [Gaussian Naive Bayes](https://towardsdatascience.com/gaussian-naive-bayes-explained-a-visual-guide-with-code-examples-for-beginners-04949cef383c) · [Decision Tree Classifier](https://towardsdatascience.com/decision-tree-classifier-explained-a-visual-guide-with-code-examples-for-beginners-7c863f06a71e) · [Logistic Regression](https://towardsdatascience.com/logistic-regression-explained-a-visual-guide-with-code-examples-for-beginners-81baf5871505) · [Support Vector Classifier](https://towardsdatascience.com/support-vector-classifier-explained-a-visual-guide-with-mini-2d-dataset-62e831e7b9e9) · [Multilayer Perceptron](https://towardsdatascience.com/multilayer-perceptron-explained-a-visual-guide-with-mini-2d-dataset-0ae8100c5d1c)
Imagine a method that makes predictions by looking at the most similar examples it has seen before. This is the essence of the Nearest Neighbor Classifier – a simple yet intuitive algorithm that brings a touch of real-world logic to Machine Learning.
While the dummy classifier sets the bare minimum performance standard, the Nearest Neighbor approach mimics how we often make decisions in daily life: by recalling similar past experiences. It's like asking your neighbors how they dressed for today's weather to decide what you should wear. In the realm of data science, this classifier examines the closest data points to make its predictions.
Definition
A K Nearest Neighbor classifier is a machine learning model that makes predictions based on the majority class of the K nearest data points in the feature space. The KNN algorithm assumes that similar things exist in close proximity, making it intuitive and easy to understand.
