Healthy user bias - Healthy user bias occurs when people who choose a preventive intervention differ from nonusers in other health-related behaviors or characteristics that...
Heaps's law - Heaps's law is an empirical relationship describing how the number of distinct terms in a text collection tends to grow as more word occurrences are observed.
Hearst patterns - Hearst patterns are recurring word-and-grammar patterns used to identify possible hyponym relationships in text: relationships in which one concept is a...
Heatmap - A heatmap is a visualization that represents numerical values using color.
Heavy-tailed distribution - A heavy-tailed distribution assigns substantial probability to extreme values because its tail is not exponentially bounded.
Hebbian learning - Hebbian learning is a family of learning ideas in which a connection changes according to the activity of the units it connects.
Heckman correction - The Heckman correction is a statistical method for estimating an outcome relationship when outcomes are observed for a nonrandomly selected subset of a...
Helmholtz machine - A Helmholtz machine is a probabilistic neural model that pairs a top-down generative network with a bottom-up recognition network.
Hermitian - A square matrix is Hermitian when it equals its conjugate transpose: A = Aᴴ.
Hessian - The Hessian of a scalar-valued function is the matrix of its second-order partial derivatives.
Heterogeneity of variance - Heterogeneity of variance means that the populations or conditional distributions being compared have different variances.
Heterogeneous subsamples - Heterogeneous subsamples are distinct subsets within a dataset whose characteristics or statistical relationships differ.
Heterogeneous treatment effect - A heterogeneous treatment effect is a causal effect that varies across individuals, groups or contexts.
Heteroskedasticity-consistent standard errors - Heteroskedasticity-consistent standard errors estimate regression-coefficient uncertainty while allowing error variance to differ across observations.
Heuristic - A heuristic is a practical rule or method used to reach a useful answer or guide a decision with limited effort.
Heuristic function - A heuristic function assigns a numerical estimate that helps guide a search.
Heuristic search - Heuristic search uses problem-specific estimates or evaluation rules to guide which candidates a search explores.
Hidden algebra - Hidden algebra is a mathematical approach to specifying and reasoning about stateful systems through their observable behavior rather than their internal...
Hidden layer - A hidden layer is an intermediate layer of a neural network between the supplied input and the final output.
Hidden Markov Decision Tree - A Hidden Markov Decision Tree is a hybrid model that grows a decision tree over sequential data, with hidden states at the nodes, so that each branch of the...
Hidden Markov model - A Hidden Markov model (HMM) is a probabilistic model for a sequence of observations generated by an unobserved sequence of states.
Hidden Markov Model with Duration - A Hidden Markov Model with Duration is a sequence model that extends the classic hidden Markov model by explicitly modeling how long the system stays in...
Hidden Markov random field - A Hidden Markov random field is a model for data arranged in a grid or network, most often images, where hidden labels at each location depend on their...
Hidden Markov Segment Model - A Hidden Markov Segment Model is a sequence model that treats observations as arriving in variable-length segments, each generated as a unit by one hidden...
Hidden representation - A hidden representation is an internal set of values a model computes while transforming an input into an output.
Hidden semi-Markov model - A hidden semi-Markov model, or HSMM, is a probabilistic model for sequences in which unobserved states can have explicitly modeled durations.
Hidden units - Hidden units are computational units inside a neural network, between its inputs and its final outputs.
Hierarchical Bayesian model - A hierarchical Bayesian model describes related quantities through multiple connected levels of probability distributions.
Hierarchical Classification - Hierarchical Classification is classification into a taxonomy of categories that sit inside one another, where a prediction can name a broad class, a...
Hierarchical clustering - Hierarchical clustering is clustering that builds a tree of groupings, from every item in its own cluster up to everything in one cluster, so you can cut...
Hierarchical control system - A hierarchical control system organizes control responsibilities into levels, with higher levels setting broader goals and lower levels handling more...
Hierarchical Data Model - The hierarchical data model organizes records through parent-child relationships arranged as a tree.
Hierarchical decomposition - Hierarchical decomposition breaks a complex task into smaller tasks arranged across levels of detail.
Hierarchical hidden Markov model - A hierarchical hidden Markov model, or HHMM, is a probabilistic sequence model whose hidden states are organized into nested levels.
Hierarchical Language Model - A Hierarchical Language Model organizes some aspect of language modeling into multiple levels, such as word classes and words, characters and words, or...
Hierarchical log-linear model - A hierarchical log-linear model describes expected counts in a contingency table through a linear model for their logarithms, with a hierarchy rule for...
Hierarchical lookahead - Hierarchical lookahead is planning ahead using actions or states represented at multiple levels of abstraction.
Hierarchical navigable small world - Hierarchical navigable small world, usually abbreviated HNSW, is a graph-based method for approximate nearest-neighbor search.
Hierarchical reinforcement learning - Hierarchical reinforcement learning is an approach to learning sequential decisions at more than one level of abstraction.
Hierarchical (sequential) sums of squares - Hierarchical (sequential) sums of squares measure how much residual squared error decreases as terms enter a linear model in a specified order.
Hierarchical softmax - Hierarchical softmax represents a probability distribution over many output classes by arranging them as leaves of a tree and multiplying conditional branch...
Hierarchical temporal memory - Hierarchical temporal memory, or HTM, is a family of machine-intelligence models inspired by proposed principles of neocortical computation.
Hierarchical variational autoencoder - A hierarchical variational autoencoder is a variational autoencoder whose generative model contains multiple dependent layers or groups of latent variables.
Hierarchical variational posterior - A hierarchical variational posterior is an approximate posterior distribution constructed with additional layers of random variables or randomized...
High-dimensional regime - The high-dimensional regime is a statistical setting in which model dimensionality is large relative to the amount of training information.
High-dimensional statistics - High-dimensional statistics studies estimation, prediction, and inference when the number of variables or model parameters is large relative to the...
High frequency data - High frequency data are observations recorded at short time intervals relative to the process being studied.