Archive for the ‘Example’ tag
Example of Nearest Neighbor Technique in Data Mining
A simple example of the nearest neighbor prediction algorithm is that if you look at the people in your neighborhood (in this case those people that are in fact geographically near to you). You may notice that, in general, you all have somewhat similar incomes. Thus if your neighbor has an income greater than $100,000 chances are good that you too have a high income. Certainly the chances that you have a high income are greater when all of your neighbors have incomes over $100,000 than if all of your neighbors have incomes of $20,000. Within your neighborhood there may still be a wide variety of incomes possible among even your “closest” neighbors but if you had to predict someone’s income based on only knowing their neighbors you’re best chance of being right would be to predict the incomes of the neighbors who live closest to the unknown person.
The nearest neighbor prediction algorithm works in very much the same way except that “nearness” in a database may consist of a variety of factors not just where the person lives. It may, for instance, be far more important to know which school someone attended and what degree they attained when predicting income. The better definition of “near” might in fact be other people that you graduated from college with rather than the people that you live next to.
Nearest Neighbor techniques are among the easiest to use and understand because they work in a way similar to the way that people think – by detecting closely matching examples. They also perform quite well in terms of automation, as many of the algorithms are robust with respect to dirty data and missing data. Lastly they are particularly adept at performing complex ROI calculations because the predictions are made at a local level where business simulations could be performed in order to optimize ROI. As they enjoy similar levels of accuracy compared to other techniques the measures of accuracy such as lift are as good as from any other.