Statistics

Normal distribution

The normal distribution, also called the Gaussian distribution, is a continuous probability distribution defined by two parameters, a mean and a variance ,...

Mathematics

Outlier Detection

Outlier detection is the process of identifying data points, observations, or patterns that deviate so markedly from the rest of a dataset that they are likely...

Data & DatasetsMachine Learning

Outliers

See also: machine learning terms, anomaly detection, robust statistics, data preprocessing An outlier is a data point that differs so markedly from the rest of...

Machine Learning

Participation Bias

Participation bias is a systematic error that arises when the individuals who choose to take part in a study, survey, or data collection effort differ in...

Data & DatasetsMachine Learning

Pattern Recognition

Pattern recognition is the automatic discovery of regularities in data through the use of computer algorithms, and the use of those regularities to take...

Artificial IntelligenceComputer Science

Principal Component Analysis (PCA)

Principal component analysis (PCA) is an unsupervised learning technique for dimensionality reduction that identifies the orthogonal directions of maximum...

Machine LearningMathematics

Prior belief

See also: Bayes' theorem, Bayesian inference, Posterior, Likelihood A prior belief, also called the prior distribution or simply the prior, is the probability...

Machine Learning

Probabilistic Regression Model

A probabilistic regression model (also called distributional regression) is a regression model that outputs a full probability distribution over possible...

Machine Learning

Quantile

A quantile is a cut point that divides a probability distribution or a sorted dataset into intervals containing equal portions of the probability or the...

Machine Learning

R (programming language)

R is a free, open-source programming language and software environment for statistical computing and graphics. It was created by Ross Ihaka and Robert...

Machine LearningProgramming Languages

Rank (ordinality)

See also: Machine learning terms In machine learning and statistics, rank or ordinality describes data whose values have a meaningful order but whose spacing...

Regression (statistics and machine learning)

Regression is a family of statistical and machine learning methods for modelling the relationship between a numeric outcome variable and one or more...

Machine Learning

Rejection sampling

Rejection sampling, also called the accept-reject method or the acceptance-rejection method, is a Monte Carlo technique that draws independent samples from a...

Machine Learning

Ridge Regularization

Ridge regularization, also known as L2 regularization or Tikhonov regularization, is a technique in statistics and machine learning that adds a squared L2-norm...

Machine LearningTraining & Optimization

Root Mean Squared Error (RMSE)

Root Mean Squared Error (RMSE), also known as root mean square deviation (RMSD), is a regression evaluation metric equal to the square root of the average of...

Machine LearningModel Evaluation

Sampling Bias

Sampling bias is a systematic error in statistics and machine learning that occurs when a sample is collected so that some members of the intended population...

AI EthicsData & Datasets

Sampling with replacement

Sampling with replacement is a method of drawing items from a population in which each selected item is returned to the pool before the next draw, so the same...

Score matching

Score matching is a method for fitting a probabilistic model by matching the gradient of its log-density, the so-called score function , to the same gradient...

Diffusion ModelsMachine Learning

Selection Bias

Selection bias is a systematic error that occurs when the data used for analysis, training, or evaluation does not accurately represent the population or...

AI EthicsData & Datasets

Squared Loss

Squared loss, also called quadratic loss, L2 loss, or squared error loss, is a loss function that penalizes a prediction by the square of its error: for a true...

Machine LearningTraining & Optimization

Stationarity

Stationarity is a property of a time series or stochastic process whose statistical characteristics, such as the mean, variance, and autocovariance, do not...

Machine Learning

Statistical learning theory

Statistical learning theory (SLT) is the mathematical framework that explains when and why machine learning algorithms generalize from a finite training sample...

Machine LearningMathematics

Subsampling

Subsampling is the practice of drawing a smaller subset from a larger collection of data points, training examples, features, or signal values, in order to cut...

Machine Learning

Temperature sampling

Temperature sampling is the most common decoding control in large language models: a single hyperparameter, written T, that divides the model's output logits...

AI Inference

Temporal data

See also: Machine learning terms Temporal data is data where each observation is tagged with a timestamp, so the order in which observations arrive carries...

Machine Learning

Time Series Analysis

Time series analysis is the statistical and computational study of data points indexed in chronological order, with the goal of extracting patterns such as...

Data ScienceMachine Learning

Topic model

A topic model is a statistical model that discovers the abstract "topics" hidden in a collection of documents, where each document is represented as a mixture...

Machine LearningNatural Language Processing

True negative

A true negative (TN) is a case that a binary classification model correctly predicts as belonging to the negative class: the true label is negative and the...

Machine LearningModel Evaluation

True positive

A true positive (TP) is a prediction that is correctly positive: the model predicts the positive class and the true label is also positive.[^1][^3][^17] It is...

Machine LearningModel Evaluation

Undersampling

Undersampling is a class imbalance handling technique in machine learning that removes examples from the majority class of a training set so the minority class...

Machine Learning

Uplift Modeling

Uplift modeling (also called incremental modeling, true lift modeling, or net modeling) is a set of machine learning and statistical techniques that predict...

Data ScienceMachine Learning

Variational Inference

Variational inference (VI), also called variational Bayes (VB), is a method in machine learning and statistics that approximates an intractable posterior...

Machine Learning

Wisdom of the Crowd

Wisdom of the crowd is the observation that the aggregate judgment of a large group of individuals often produces more accurate estimates or decisions than any...

Machine Learning