Enum OutputDistribution

Namespace

AiDotNet.Enums

Assembly

AiDotNet.dll

Specifies the target distribution for quantile transformation.

public enum OutputDistribution

Fields

Normal = 1

Maps data to a normal (Gaussian) distribution with mean 0 and standard deviation 1. Values follow a bell curve pattern.

For Beginners: This makes your data look like a bell curve - most values are near the middle, with fewer values at the extremes. Many statistical methods assume this distribution.

Use this when: - Your algorithm assumes normally distributed features (e.g., linear regression, LDA) - You want to reduce the impact of outliers while maintaining statistical properties - You need compatibility with methods that expect Gaussian distributions

Uniform = 0

Maps data to a uniform distribution where all values are equally likely. Values are spread evenly across the [0, 1] range.

For Beginners: This makes your data look like a flat line - every value is equally common. Good for algorithms that don't assume any particular distribution.

Use this when: - You want to reduce the impact of outliers - Your algorithm works best with uniformly distributed features - You want a simple, predictable transformation

Remarks

This enum defines the available output distributions for the QuantileTransformer. Each distribution has different characteristics and use cases in machine learning.

For Beginners: Think of this as choosing the shape you want your data to take: - Uniform: Spreads values evenly across the range (like a flat distribution) - Normal: Creates a bell curve pattern (most values in the middle, fewer at extremes)