Spike-and-slab regression
Definition
Spike-and-slab regression is a Bayesian statistical technique used for variable selection …
Statistics
Regularization
Definition
Regularization is a crucial concept in machine learning designed to reduce generalization …
Rademacher complexity
Definition
Rademacher complexity evaluates how well a hypothesis class can correlate with random …
Phi coefficient
Definition
The Phi coefficient (φ) is a measure of association for two binary variables, serving as …
Perception error model
Definition
A perception error model describes the discrepancies between observed sensory data and …
Linear predictor function
Definition
In statistical modeling and machine learning, a linear predictor function represents the …
Leave-one-out cross-validation
Definition
Leave-one-out cross-validation (LOOCV) is a specific case of k-fold cross-validation …
Life-time of correlation
Definition
In dynamic systems and time-series analysis, the life-time of correlation measures the …
Learnable function class
Definition
In statistical learning theory, a learnable function class represents the hypothesis …
Kernel density estimation
Definition
Kernel Density Estimation (KDE) is a fundamental statistical technique that smooths …
GLM
Definition
In statistical modeling, GLM stands for Generalized Linear Models, which extend linear …
Generalized additive model for location, scale and shape
Definition
Unlike traditional regression models that focus only on the mean, GAMLSS models the …
Feature scaling
Definition
Feature scaling standardizes the range of input variables to prevent features with larger …
Empirical dynamic modeling
Definition
Empirical Dynamic Modeling (EDM) is a framework for analyzing nonlinear dynamical systems …
EM algorithm and GMM model
Definition
This term refers to the synergistic relationship between the Expectation-Maximization …
Dataset shift
Definition
Dataset shift occurs when the distribution of data used to train a machine learning model …
Data-driven model
Definition
A data-driven model is a type of artificial intelligence system where behavior and …
Data Science and Predictive Analytics
Definition
Data science involves the interdisciplinary process of extracting knowledge from …
Cross-validation
Definition
Cross-validation is a statistical method used to estimate the skill of machine learning …
Category utility
Definition
This metric quantifies how well a set of categories allows one to predict the values of …
Bradley–Terry model
Definition
The Bradley-Terry model is a probabilistic model widely used in psychometrics and machine …
Bias–variance tradeoff
Definition
The bias-variance tradeoff describes the tension between underfitting (high bias) and …
Base rate
Definition
In statistics and machine learning, the base rate refers to the underlying frequency of a …
Astrostatistics
Definition
Astrostatistics is a specialized field that bridges statistics and astronomy. It involves …
A/B Testing
Definition
A/B testing is a randomized controlled experiment where two variants, A and B, are …
Prior
Definition
A ‘prior’ represents existing beliefs or historical data regarding a variable …
Monte
Definition
Monte Carlo techniques are a class of computational algorithms that rely on repeated …
Gaussian
Definition
Gaussian refers to the normal distribution, a continuous probability distribution …
Causal
Definition
In artificial intelligence, causal modeling seeks to understand how interventions on one …
Carlo
Definition
Monte Carlo methods are essential techniques in AI and statistics for approximating …
Bayesian
Definition
Bayesian approaches in AI use probability theory to update the likelihood of hypotheses …