Conditional Probability from Joint Distribution
Probability Theory DS practice problem on Onlearn.
Difficulty: medium.
Topics: Understanding Conditional Probability from Joint Distribution, Probability Mass Functions, Conditional Probability, Column Summation, Array Broadcasting, Normalization Constants, Probability Theory, Linear Algebra, Statistics, Data Science Fundamentals, Calculus, Joint Probability Distributions, Marginalization, Bayesian Inference, Normalization, Random Variables.
Given a 2D numpy array representing the joint probability distribution P(X, Y) where rows correspond to X and columns correspond to Y, write a function that calculates the conditional probability distribution P(X | Y=y idx). The function should return a 1D array representing P(X | Y=y idx).