One of the most notable data mining techniques you can leverage is Predictive. Just as the name suggests, predictive data analysis aims to forecast outcomes based on a set of circumstances. But how much do you know about data mining analysis. If you cannot answer this question easily, then you have certainly come to the right place. In this post, we will take you through some of the most common predictive data mining techniques you ought to be fully aware of.
Regression
This predictive data mining technique mostly deals with numeric values. Thanks to regression data mining, small and large businesses alike and other institutionscan calculate things such as pricing and value without encountering any issues whatsoever. A good example of regression data mining would be predicting voter trends.One of the simplest and oldest forms of regression is linear regression. This is used to estimate a relationship between two variables.
Classification
Just as is the case with regression data mining, classification aims at yielding a predicted outcome, but of course, without a numeric value. Some of the classifications are based on things such as poor, fair, good and excellent. Keep in mind the main goal of classification is to predict the target class accurately for each case in the data.
To test out classification models, you need to compare the predicted values to know target values. This is done in a set of test data. Just in case you did not know, classification projects are divided into two data sets i.e. one for testing the model, and the other for building the model.
The Bottom Line
There you have it, some of the things you need to know about predictive data mining techniques. Fortunately, you can leverage the internet to find out more about what it entails. If you’re still finding it hard, then it would be better to seek the help of experts in the industry. Through this action, you’re going to do away with all doubts you might be having in mind regarding predictive data mining techniques.
