**K-Nearest Neighbors – the Laziest Machine Learning Technique** - Sep 12, 2017.

K-Nearest Neighbors (K-NN) is one of the simplest machine learning algorithms. When a new situation occurs, it scans through all past experiences and looks up the k closest experiences. Those experiences (or: data points) are what we call the k nearest neighbors.

Tags: Algorithms, Machine Learning, Nearest Neighbor, RapidMiner

**Neighbors Know Best: (Re) Classifying an Underappreciated Beer** - Nov 24, 2016.

A look at beer features to determine whether a specific brew might be better served (pun intended) by being classified under a different style. kNN analysis supported with in-post plots and linked iPython notebook.

Tags: Beer, Classification, Data Visualization, Nearest Neighbor, Python

**The Great Algorithm Tutorial Roundup** - Sep 20, 2016.

This is a collection of tutorials relating to the results of the recent KDnuggets algorithms poll. If you are interested in learning or brushing up on the most used algorithms, as per our readers, look here for suggestions on doing so!

Tags: Algorithms, Clustering, Decision Trees, Machine Learning, Nearest Neighbor, PCA, Poll, Random Forests, Regression, Statistics, Text Mining, Time Series, Visualization

**Implementing Your Own k-Nearest Neighbour Algorithm Using Python** - Jan 27, 2016.

A detailed explanation of one of the most used machine learning algorithms, k-Nearest Neighbors, and its implementation from scratch in Python. Enhance your algorithmic understanding with this hands-on coding exercise.

**Pages:** 1 2 3

Tags: Nearest Neighbor, Python, Python Tutorial

**Top 10 Data Mining Algorithms, Explained** - May 21, 2015.

Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.

**Pages:** 1 2 3

Tags: Algorithms, Apriori, Bayesian, Boosting, C4.5, CART, Data Mining, Explained, K-means, Nearest Neighbor, Page Rank, Support Vector Machines, Top 10

**Do We Need More Training Data or More Complex Models?** - Mar 23, 2015.

Do we need more training data? Which models will suffer from performance saturation as data grows large? Do we need larger models or more complicated models, and what is the difference?

Tags: Big Data, convnet, Generalized Linear Models, Nearest Neighbor, Zachary Lipton