Thanksgiving Feast Predictor: Softmax for Dish Selection
Representation Learning, Advanced Theory & Miscellaneous DS practice problem on Onlearn.
Difficulty: easy.
Topics: Thanksgiving Feast Predictor: Softmax for Dish Selection, Softmax Activation Function, Log-Sum-Exp Trick, One-Hot Encoding, Kullback-Leibler Divergence, Categorical Probability Distribution, Probabilistic Graphical Models, Optimization Theory, Information Theory, Statistical Learning, Computational Complexity, Multinomial Logistic Regression, Stochastic Gradient Descent, Maximum Likelihood Estimation, Cross-Entropy Minimization, Feature Engineering Pipelines.
Write a Python function to predict the probability distribution of which Thanksgiving dish a guest will choose based on their preference scores. Given a list of preference scores for different dishes (e.g., turkey, stuffing, cranberry sauce, pumpkin pie), use the softmax function to convert these scores into probabilities. The function should return a list of probabilities where each probability represents the likelihood of choosing that dish. The probabilities should sum to 1.