data normalization techniques

Data normalization techniques are methods used to adjust data values so they are on a common scale, making comparisons and analysis more meaningful. For example, Min-Max normalization rescales data to a specific range, usually 0 to 1, by subtracting the minimum value and dividing by the range. Z-score normalization transforms data based on the mean and standard deviation, resulting in values centered around zero. These techniques help improve the performance of algorithms that are sensitive to data scale, ensuring that no single feature disproportionately influences the analysis.