By Kardi Teknomo, PhD.

K Nearest Neighbor e-book

What is K Nearest Neighbor?

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. When you purchase this tutorial, you will also get the spreadsheet companion of this tutorial. First, you will learn KNN for classification, and then you will learn the same method is extended for smoothing and solving time series data. The numerical example are complete until final solution.

Your Benefit

You have read our sample of FREE tutorial this far. Our tutorial has given you FAST and SIMPLE understanding about the topic. Unlike many other books and tutorials out there, we only serve you the main course. Our tutorials always have comprehensive examples that teach you step by step on how to do it. Do you want to gain BETTER understanding about this topic? Do you want to know more on how to do it on your own? You need to download the companion file of this tutorial. You need to download the full version of this tutorial.

Why do you need to download this e-book and its companion files NOW?

  • Gain full understanding . Your memory about your new understanding about this fascinating topic is still fresh. If you download it now, you will easily understand the detail of the tutorial. If you do it next time, you might have forgotten the understanding that has gained today.
  • Save your learning time . Your time is very valuable. It saves a lot of your time to do self study on this topic.
  • Understanding this topic will enhance your study , your work, and your research. Eventually you can develop it further to get more money for your future.
  • Tired of ads? By purchasing the FULL tutorial, you will be able to read tutorial in a very nice PDF format without advertising . You can zoom in and out to see the formulas clearly. You can read in any computing device (phone, tablet, PC, laptop, Mac, iPad).
  • The full tutorial also comes in e-book together with the companion files . This option will give you an eye opener to this fascinating topic. It enhances your understanding. The complete tutorial will be your self-study guide to improve your learning process. You can read it off-line anywhere anytime even when you don't have internet connection.

What you will get when you download this KNN tutorial NOW?

In this K Nearest Neighbor Tutorial e-book you will learn, you will learn the following fascinating topics in a very SHORT TIME:

  • What is K-Nearest Neighbor (KNN) Algorithm? KNN ebook
  • How K-Nearest Neighbor (KNN) Algorithm works?
  • KNN Numerical Example (hand computation)
  • How to use KNN for Smoothing?
  • Step by step Example solving KNN for Interpolation
  • How to use KNN for Time Series Prediction?
  • Comprehensive Example KNN for Extrapolation
  • How do we use spreadsheet for KNN?
  • Strength and Weakness of K-Nearest Neighbor Algorithm

See the comparison table below for the options.


Features

Options

Only Companion File

Complete Tutorial (Best Buy)

Three MS Excel Workbooks on K Nearest Neighbor for

  • classification
  • smoothing (interpolation)
  • time series prediction (extrapolation)

Available

Available

Free 1 year update of companion files

Available

Available

Free 1 year update of K Nearest Neighbor Tutorial

Available

Nice format of e-book of K Nearest Neighbor Tutorial in PDF format

Available

Discounted Price

ONLY $2.49

ONLY $3.99

Buy Now (secure purchase through PayPal)

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The price of our tutorial is so cheap that it is probably even cheaper than the cost of your lunch.

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Teachers who want to use this e-book or the companion files for students in a class can contact us to purchase the e-book license in bulk.

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