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This tutorial is an introduction to an instance based learning called K-Nearest Neighbor or KNN algorithm. KNN is part of supervised learning that has been used in many applications in the field of data mining, statistical pattern recognition, image processing and many others. Some successful applications are including recognition of handwriting, satellite image and EKG pattern. Instead of using sophisticated software or any programming language, I will use only spreadsheet functions of Microsoft Excel, without any macro. If you purchase the ebook of this tutorial, you can download the spreadsheet companion of this tutorial.

First, you will learn KNN for classification , then we will extend the same method for smoothing and prediction in solving time series data.

Topics of this tutorial are:

What is K-Nearest Neighbor (KNN) Algorithm ?Give your feedback and rate this tutorial

How K-Nearest Neighbor (KNN) Algorithm works?

Numerical Example (hand computation)

KNN for Smoothing and Prediction

KNN for Interpolation, SmoothingHow do we use the spreadsheet for KNN?

KNN for Extrapolation, Prediction, Forecasting

Strength and Weakness of K-Nearest Neighbor Algorithm

Resources for K Nearest Neighbors Algorithm

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See Also
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K means clustering
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Similarity Measurement
,
Reinforcement Learning (Q-Learning)
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Discriminant Analysis
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Kernel Regression
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Clustering
,
Decision Tree

This tutorial is copyrighted .

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Preferable reference for this tutorial is
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Teknomo, Kardi. K-Nearest Neighbors Tutorial. http:\\people.revoledu.com\kardi\tutorial\KNN\