Data Normalization -

What is Data Normalization - Data normalization is a technique used in data mining to transform the values of a dataset into a common scale. This is important because many machine learning algorithms are sensitive to the scale of the input features and can produce better results when the data is normalized.

Data Normalization Techniques -  

Min-Max Normalization -  This technique performs a linear transformation on the original data. It scales the values of a feature to a range between 0 and 1. This is done by subtracting the minimum value of the feature from each value, and then dividing by the range of the feature. The formula for min-max normalization is:

Z-Score Normalization -  Also known as Zero mean normalization or standardization, this technique normalizes values based on the mean and standard deviation of the data. Each value is replaced by a score that indicates how many standard deviations it is from the mean. You can apply Z-score normalization using the following formula:

Decimal Scaling Normalization -  This technique normalizes by moving the decimal point of values of the data. Each value of the data is divided by the maximum absolute value of the data, resulting in values typically in the range of -1 to 1. The formula for this simple normalization technique is:

Advantages:

1. Improved performance of machine learning algorithms: Normalization can help to improve the performance of machine learning algorithms by scaling the input features to a common scale.
2. Better handling of outliers: Normalization can help to reduce the impact of outliers by scaling the data to a common scale, which can make the outliers less influential.

Disadvantages:

1. Loss of information: Normalization can result in a loss of information if the original scale of the input features is important.
2. Additional computational costs: Normalization can add additional computational costs to the data mining process, as it requires additional processing time to scale the data.

Source - https://www.geeksforgeeks.org/data-normalization-in-data-mining/

https://estuary.dev/data-normalization