Pattern Recognition
Pattern recognition is the automatic discovery of regularities in data through the use of computer algorithms
Statistics
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Principal Component Analysis (PCA)
Principal component analysis (PCA) is an unsupervised learning technique for dimensionality reduction that identifies the orthogonal directions of maximum variance in high-dimensional data and projects…
Prior belief
A prior belief, also called the prior distribution or simply the prior, is the probability distribution that expresses what is known or assumed about an unknown parameter before any data is observed.
Probabilistic Graphical Model
A probabilistic graphical model (PGM) is a mathematical representation in which a graph expresses the factorization and conditional-independence structure of a probability distribution.
Probabilistic Regression Model
A probabilistic regression model (also called distributional regression) is a regression model that outputs a full probability distribution over possible target values rather than a single point estimate.
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 observations.
R (programming language)
R is a free, open-source programming language and software environment for statistical computing and graphics.
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 explanatory variables (often called predictors, features, or…
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 hard-to-sample target distribution p(x) by…
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 penalty to a model's loss function.
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 the squared differences between predicted and…
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 have a higher or lower probability of being…
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 $$\nabla_x \log p(x)$$, to the same gradient of the data distribution
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 domain it is intended to describe
Simulated annealing
Simulated annealing is a probabilistic method for finding a good approximate solution to a global optimization problem, especially one with many local optima that trap ordinary hill-climbing methods.
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 value $y$ and a prediction $\hat{y}$
Stationarity
Stationarity is a property of a time series or stochastic process whose statistical characteristics, such as the mean, variance, and autocovariance, do not change when the series is shifted in time.
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 to unseen data.
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 compute cost, add regularization, or rebalance a…
Temporal data
Temporal data is data where each observation is tagged with a timestamp, so the order in which observations arrive carries meaning.
Time Series
A time series is a sequence of observations recorded in time order, often at regular intervals: daily retail sales, hourly electricity demand, per-minute server latency, quarterly GDP.
Time Series Analysis
Time series analysis is the statistical study of ordered observations when dependence across time is part of the signal rather than a nuisance to ignore.
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 of a small number of latent topics and each topic…
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 predicted label is also negative.
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.
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 is no longer drowned out.
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 the incremental impact of a treatment or action on…
VC dimension
The Vapnik-Chervonenkis dimension, almost always shortened to VC dimension, measures the capacity of a class of binary classifiers by asking how many points the class can label in every possible way.
Variational Inference
Variational inference (VI), also called variational Bayes (VB), is a method in machine learning and statistics that approximates an intractable posterior distribution by turning Bayesian inference into an…
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 single member of that group