Author: maxalex
Preprocessing / Feature Extraction
Credit Assignment Problem Sum-of-Squares Error Function Model Comparison / Model Selection Effective Number of Parameters Validation Set / Hold-Out Set Probability Density over x Cumulative Distribution Function Probability Mass Function Densities and Continuous Variables Expectations & Covariances Variance of the variable x Classical / Frequentist interpretation of probablity The Guassian Distribution Guassian / Normal Distribution Mean, Variance, Standard Deviation, Precision Independent & Identically distributed Gaussian Noise Distribution Sum of Squares Error Function Akaike Information Criterion Bayesian Information Criterion The Curse of Dimensionality Cartesian vs. Polar Coordinates Reasons for effective techniques in high dimensional data Subject of Decision Theory
Extract any quantities in Bayes Theorem
Minimizing the missclassification rate Decision Boundaries or Surfaces Minimizing the expected loss Loss, Cost and Utility Function Simple way for Prior Calculation Advantages of Posterior Probability Estimation (4) Loss functions for regression Loss function in regression Irreducible Minimum Value of Loss Function Three distinct Approaches Poor Results of Squared Loss Idea of Information Theory Definition of Information Microstate, Macrostate, weight of Macrostate Maximum Entropy Configuration Maximum of Differential Entropy Negativity of Differential Entropy Relation between differential & conditional entropy Relative entropy & mutual information Rlative Entropy / KL divergence Properties of KL divergence Relationship to Data Compression Relation of MI to Conditional Entropy