# Normalization with decimal scaling in data mining – Examples

Last modified on December 9th, 2018 at 9:20 pm

**Decimal scaling with Examples**

Decimal scaling is a data normalization technique. In this technique, we move the decimal point of values of the attribute. This movement of decimal points totally depends on the maximum value among all values in the attribute.

**The formula of decimal scaling:**

A value v of attribute A is can be normalized by the following formula

Normalized value of attribute = **( v ^{i} / 10^{j} )**

## Example of Decimal scaling :

CGPA | Formula | CGPA Normalized after Decimal scaling |

2 | 2/10 | 0.2 |

3 | 3/10 | 0.3 |

** Try our Automatic Tool to normalize the data **

We will check maximum value among our attribute CGPA. Here maximum value is 3 so we can convert it to a decimal by dividing by 10. Why 10?

we will count total numbers in our maximum value and then put 1 and after 1 we can put zeros equal to the length of the maximum value.

Here 3 is the maximum value and total numbers in this value are only 1. so we will put one zero after one.

**Example 2:**

Salary bonus | Formula | CGPA Normalized after Decimal scaling |

400 | 400 / 1000 | 0.4 |

310 | 310 / 1000 | 0.31 |

We will check the maximum value of our attribute “**salary bonus**“. Here maximum value is 400 so we can convert it into a decimal by dividing with 1000. Why 1000?

400 contains three digits and we so we can put three zeros after 1. So, it looks like 1000.

**Example 3:**

Salary | Formula | CGPA Normalized after Decimal scaling |

40,000 | 40,000 / 100000 | 0.4 |

31, 000 | 31,000 / 100000 | 0.31 |