PROB_THEORY
Bayes' Theorem
Updating beliefs based on new evidence. The cornerstone of probabilistic machine learning.
P(A|B) = P(B|A)P(A) / P(B)Distributions
Normal, Poisson, Binomial - understanding how data clusters and spreads.
DATA_VARIANCE
STANDARD_DEVIATION
σ = √[Σ(x-μ)² / N]
Measuring the uncertainty and spread of information.
ANALYSIS_KIT
Z-Scores
Standardizing dataset values.
P-Values
Statistical significance mapping.
Regression
Predictive linear modeling.
Entropy
Information gain and uncertainty.