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The normalization model is an influential model of responses of neurons in primary visual cortex. David Heeger developed the model in the early 1990s,
Normalization_model
Reduction of data redundancy
British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations)
Database_normalization
Data modeling concept
descriptive (dimension) tables Developers often don't normalize dimensions due to several reasons: Normalization makes the data structure more complex Performance
Dimensional_modeling
Topics referred to by the same term
or regular. Normalization process theory, a sociological theory of the implementation of new technologies or innovations Normalization model, used in visual
Normalization
Machine learning technique
learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization and activation
Normalization (machine learning)
Normalization_(machine_learning)
Social processes through which ideas and actions come to be seen as normal
France in 1978, Foucault defined normalization thus: Normalization consists first of all in positing a model, an optimal model that is constructed in terms
Normalization_(sociology)
Sociological model
and contextual integration. This model helped build the normalization process theory. The normalization process model is a theory that explains how new
Normalization_process_model
Database data model
data model (organization of data in a database) which does not meet any of the conditions of database normalization defined by the relational model. Database
Unnormalized_form
Centralized storage of knowledge
use of database normalization and an entity–relationship model. Operational system designers generally follow database normalization to ensure data integrity
Data_warehouse
Sociological theory
chararacterised normalization process theory as a trial killer. Through three iterations, the theory has built upon the normalization process model previously
Normalization_process_theory
Statistical model used in machine learning
generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, which
Flow-based_generative_model
Analytic tools in disability studies
described as a fixer/fixee relationship. The medical model, also known as the normalization model, views disability as a medical disorder, in need of treatment
Models_of_disability
Offering the same conditions as are offered to other citizens
of life or society." Normalization is a rigorous theory of human services that can be applied to disability services. Normalization theory arose in the
Normalization_principle
Mathematical description of quantum state
system's degrees of freedom must be equal to 1, a condition called normalization. Since the wave function is complex-valued, only its relative phase
Wave_function
Statistical technique for producing prediction sets
ŷ-values Optional: if using a normalized nonconformity function Train the normalization ML model Predict normalization scores → 𝜺 -values Compute the
Conformal_prediction
Technique for the generative modeling of a continuous probability distribution
diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable generative models. A diffusion
Diffusion_model
Case of database modeling
considered different from dimensional modeling and complementary to database normalization. The SQL:2011 standard provides language constructs for working with
Bitemporal_modeling
Type of machine learning model
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation
Large_language_model
Large language model by Meta AI
(2016-07-01). "Layer Normalization". arXiv:1607.06450 [stat.ML]. Zhang, Biao; Sennrich, Rico (2019-10-01). "Root Mean Square Layer Normalization". arXiv:1910
Llama_(language_model)
Method used to normalize the range of independent variables
method used to normalize the range of independent variables or features of data. In data processing, it is also known as data normalization and is generally
Feature_scaling
Estimator for quality of a statistical model
quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to each
Akaike_information_criterion
Method of improving artificial neural network
In artificial neural networks, batch normalization (also known as batch norm) is a normalization technique used to make training faster and more stable
Batch_normalization
Level of database normalization
to Database Normalization by Mike Hillyer. A tutorial on the first 3 normal forms by Fred Coulson Description of the database normalization basics by Microsoft
Second_normal_form
normalization formula is the following: tfn = tf * log(1 + c*(sl/dl)) (normalization 2) Normalization 2 is usually considered to be more flexible, since there is
Divergence-from-randomness model
Divergence-from-randomness_model
Agile database modeling technique
through extensions. The high degree of normalization makes it possible to non-destructively add the necessary modeling concepts needed to capture a change
Anchor_modeling
Logical arrangement of computing tables in a multidimensional database
these schemas are not normalized much, and are frequently designed at a level of normalization short of third normal form. Normalization splits up data to
Snowflake_schema
Level of database normalization
358054. Litt's Tips: Normalization Database Normalization Basics by Mike Chapple (About.com) An Introduction to Database Normalization by Mike Hillyer. A
Third_normal_form
and D.J. Heeger, Normalization as a canonical neural computation. Nat Rev Neurosci, 2012. 13(1): p. 51-62. Heeger, D.J., Normalization of cell responses
David_Heeger
How many standard deviations apart from the mean an observed datum is
score is called standardizing or normalizing (however, "normalizing" can refer to many types of ratios; see Normalization for more). Standard scores are
Standard_score
Algorithm for modelling sequential data
residual connections and layer normalization steps. These feed-forward layers contain most of the parameters in a transformer model. The feedforward network
Transformer_(deep_learning)
Used to assess the predictive power of hydrological models
NSE to lie solely within the range of {0,1} normalization, use the following equation that yields a Normalized Nash–Sutcliffe Efficiency (NNSE) NNSE = 1
Nash–Sutcliffe model efficiency coefficient
Nash–Sutcliffe_model_efficiency_coefficient
Model for generating observable data in probability and statistics
Generative models are a class of computational models frequently used for classification. In machine learning, it typically models the joint distribution
Generative_model
Numerical relationship among rows in different tables
process of database normalization ends up breaking tables into a larger number of smaller tables. In the real world, data modeling is critical because
Cardinality_(data_modeling)
Relative measure of dispersion expressed as the ratio of standard deviation to the mean
ratio, but is not dimensionless, and hence not scale invariant. See Normalization (statistics) for further ratios. In signal processing, particularly
Coefficient_of_variation
Class of statistical survival models
Proportional hazards models are a class of survival models in statistics. Survival models relate the time that passes, before some event occurs, to one
Proportional_hazards_model
Statistical model for a binary dependent variable
In statistics, a logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent
Logistic_regression
Strategy used on previously-normalized databases
denormalization benefits can only be fully realized on a data model that is otherwise normalized. A normalized design will often "store" different but related pieces
Denormalization
Designing how data is held in a database
[1] [2] Database Normalization Basics Archived 2007-02-05 at the Wayback Machine by Mike Chapple (About.com) Database Normalization Intro Archived 2011-09-28
Database_design
Covariance and correlation
normalization is usually dropped and the terms "cross-correlation" and "cross-covariance" are used interchangeably. The definition of the normalized cross-correlation
Cross-correlation
Statistical hypothesis test
the Pearson distribution to model the observation and performing a test of goodness of fit to determine how well the model really fits to the observations
Chi-squared_test
American psychologist and professor
entitled Perceived Number Equivalence By Adults And Children: A Normalization Model Of Size-Density Coordination. While completing his graduate degrees
Richard_Pringle
Statistical measure
models with different scales. Though there is no consistent means of normalization in the literature, common choices are the mean or the range (defined
Root_mean_square_deviation
Form of causal modeling that fit networks of constructs to data
Structural equation modeling (SEM) is a diverse set of methods used by scientists for both observational and experimental research. SEM is used mostly
Structural_equation_modeling
American neuroscientist
Neuron (journal) describing a model for studying attentional selection in the brain, which was dubbed the "normalization model of attention." In 2013, he
John Reynolds (neuroscientist)
John_Reynolds_(neuroscientist)
Statistical property
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Standard_error
Measure of the shape of a function
density, then the zeroth moment is the total mass, the first moment (normalized by total mass) is the center of mass, and the second moment is the moment
Moment_(mathematics)
Level of database normalization
First normal form (1NF) is the most basic level of database normalization defined by English computer scientist Edgar F. Codd, the inventor of the relational
First_normal_form
Measure of statistical dispersion
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Interquartile_range
Design of tasks
discussion of experimental design in the context of model building for models either static or dynamic models, also known as system identification. Laws and
Design_of_experiments
Type of mathematical model
A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data
Statistical_model
Image processing step or image registration method
and they are coregistered. Spatial normalization typically employs a 3-dimensional nonrigid transformation model (a "warp-field") for warping a brain
Spatial_normalization
Statistical property
it invalidates statistical tests of significance which assume that the modelling errors all have the same variance. While the ordinary least squares (OLS)
Homoscedasticity and heteroscedasticity
Homoscedasticity_and_heteroscedasticity
Number of values in the final calculation of a statistic that are free to vary
fully determined). The term is most often used in the context of linear models (linear regression, analysis of variance), where certain random vectors
Degrees of freedom (statistics)
Degrees_of_freedom_(statistics)
Statistical model for count data
statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression
Poisson_regression
Statistic measuring inter-rater agreement for categorical items
account" chance agreement. To do this effectively would require an explicit model of how chance affects rater decisions. The so-called chance adjustment of
Cohen's_kappa
Set of statistical processes for estimating the relationships among variables
In statistical modeling, regression analysis is a statistical method for estimating the relationship between a dependent variable (often called the outcome
Regression_analysis
Middle quantile of a data set or probability distribution
estimator of the population median. If data is represented by a statistical model specifying a particular family of probability distributions, then estimates
Median
Branch of statistics
reliability engineering in engineering, duration analysis or duration modelling in economics, and event history analysis in sociology. Survival analysis
Survival_analysis
Method of quality control
enterprise data quality management system. In the 1988 Capability Maturity Model (CMM), the Software Engineering Institute suggested that SPC could be applied
Statistical_process_control
Statistical measure of variability
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Median_absolute_deviation
Correlation of a signal with a time-shifted copy of itself, as a function of shift
without the normalization, that is, without subtracting the mean and dividing by the variance. When the autocorrelation function is normalized by mean and
Autocorrelation
Statistical test that compares goodness of fit
that involves comparing the goodness of fit of two competing statistical models, typically one found by maximization over the entire parameter space and
Likelihood-ratio_test
Empirical law on the variance of species in a habitat
Hanski proposed a random walk model, modulated by the presumed multiplicative effect of reproduction. Hanski's model predicted that the power law exponent
Taylor's_law
Statistical modeling method
In statistics, linear regression is a model that estimates the relationship between a scalar response (dependent variable) and one or more explanatory
Linear_regression
Topic in computer vision concerned with artificial color vision and object recognition
Color normalization is a topic in computer vision concerned with artificial color vision and object recognition. In general, the distribution of color
Color_normalization
Time series model
econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current
Autoregressive conditional heteroskedasticity
Autoregressive_conditional_heteroskedasticity
Statistical hypothesis test
two models, 1 and 2, where model 1 is 'nested' within model 2. Model 1 is the restricted model, and model 2 is the unrestricted one. That is, model 1 has
F-test
Selection of data points in statistics
so that rarer target classes will be more represented in the sample. The model is then built on this biased sample. The effects of the input variables
Sampling_(statistics)
Concept in information theory
language model is a probability distribution over entire texts or documents. Consequently, in NLP, the more commonly used measure is token-normalized perplexity
Perplexity
Diagnostic plot of binary classifier ability
graphical plot that illustrates the performance of a binary classifier model (although it can be generalized to multiple classes) at varying threshold
Receiver operating characteristic
Receiver_operating_characteristic
Experiment methodology
control mechanism. Adaptive control Between-group design experiment Choice modelling Multi-armed bandit Multivariate testing Randomized controlled trial Scientific
A/B_testing
Generates a forecast of future values of a time series
exponential smoothing models and ARIMA models with a range of nonseasonal and seasonal p, d, and q values, and selects the model with the lowest Bayesian
Exponential_smoothing
Measure of linear correlation
and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value
Pearson correlation coefficient
Pearson_correlation_coefficient
Type of average of a collection of numbers
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Arithmetic_mean
Probabilistic problem-solving algorithm
integration, and non-uniform random variate generation, available for modeling phenomena with significant input uncertainties, e.g. risk assessments for
Monte_Carlo_method
Numeric quantity representing the center of a collection of numbers
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Mean
Expression that cannot be rewritten further
strongly normalizing. The pure untyped lambda calculus does not satisfy the strong normalization property, and not even the weak normalization property
Normal form (abstract rewriting)
Normal_form_(abstract_rewriting)
Concept in inferential statistics
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Statistical_significance
Process of using data analysis for predicting population data from sample data
trained model"; in this context inferring properties of the model is referred to as training or learning (rather than inference), and using a model for prediction
Statistical_inference
Process of transforming text into a single canonical form
to be processed afterwards; there is no all-purpose normalization procedure. Text normalization is frequently used when converting text to speech. Numbers
Text_normalization
Class of statistical models
linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be
Generalized_linear_model
Graphical representation of the distribution of numerical data
The total area of a histogram used for probability density is always normalized to 1. If the length of the intervals on the x-axis are all 1, then a histogram
Histogram
Numerical measure of a statistical relationship between variables
well a statistical model fits observations by summarizing the discrepancy between observed values and the values expected under the model Multiple correlation
Correlation_coefficient
Statistical concept
size reading population has been normalized to 1. A typical finite-dimensional mixture model is a hierarchical model consisting of the following components:
Mixture_model
Type of chart
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Bar_chart
Statistical measure of association
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Cramér's_V
Function related to statistics and probability theory
statistical model explains observed data by calculating the probability of seeing that data under different parameter values of the model. It is constructed
Likelihood_function
Statistical model validation technique
rotation estimation or out-of-sample testing, is any of various similar model validation techniques for assessing how the results of a statistical analysis
Cross-validation_(statistics)
Ranking function used by search engines
different degrees of importance, term relevance saturation and length normalization. BM25F defines each type of field as a stream, applying a per-stream
Okapi_BM25
Sequence of data points over time
forecasting is the use of a model to predict future values based on previously observed values. Generally, time series data is modeled as a stochastic process
Time_series
Interpretation of probability
variables, or more generally unknown quantities, to model all sources of uncertainty in statistical models including uncertainty resulting from lack of information
Bayesian_probability
Statistical property quantifying how much a collection of data is spread out
transformation Scaling and normalization Feature scaling Normalization Standardization (z-score) Min–max normalization Unit vector normalization Data cleaning Data
Statistical_dispersion
Statistical method
of an estimator by resampling (often with replacement) one's data or a model which is estimated from the data. Bootstrapping assigns measures of accuracy
Bootstrapping_(statistics)
Measure of the joint variability
units. In those situations, we use the correlation coefficient, which normalizes the covariance to a value between -1 and 1 by dividing by the geometric
Covariance
Statistical sampling technique
Campbell, J.E. (1981). "An approach to sensitivity analysis of computer models, Part 1. Introduction, input variable selection and preliminary variable
Latin_hypercube_sampling
Scientific procedure performed to validate a hypothesis
statistical model that reflects an objective randomization, the statistical analysis relies on a subjective model. Inferences from subjective models are unreliable
Experiment
Solvable physics model
\psi _{i_{m}}} . Note that sometimes an extra normalization factor is included. The most famous model is when m = 4 {\displaystyle m=4} : H S Y K = −
Sachdev–Ye–Kitaev_model
Inverse of the average of the inverses of a set of numbers
pi's weighted by their respective distances (optionally with the weights normalized so they sum to 1 by dividing them by trip length). This gives the true
Harmonic_mean
Statistical test comparing two probability distributions
Keith; Arnold, Steven [F.] (1999). Classical Inference and the Linear Model. Kendall's Advanced Theory of Statistics. Vol. 2A (Sixth ed.). London: Arnold
Kolmogorov–Smirnov_test
Table that displays the frequency of variables
Correlation". 26 December 2019. Andersen, Erling B. 1980. Discrete Statistical Models with Social Science Applications. North Holland, 1980. Bishop, Y. M. M.;
Contingency_table
NORMALIZATION MODEL
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Girl/Female
Hindu, Indian, Traditional
Model; Idea
Female
Japanese
(1-儀, 2-典, 3-則, 4-法) Japanese unisex name NORI means 1) "ceremony, regalia," 2) "code, precedent," 3) "model, rule, standard," 4) "law, rule."
Boy/Male
Arabic, Muslim
Sample; Model; Paragon
Boy/Male
Celebrity, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Punjabi, Sanskrit, Sikh, Tamil, Telugu, Traditional
New; Role Model of World; Ever Fresh
Boy/Male
Arabic, Muslim
Pioneers; Explorers; Guides; Leaders; Models
Boy/Male
Muslim
Model, Example
Surname or Lastname
English and Irish (of Norman origin), and northern French
English and Irish (of Norman origin), and northern French : habitational name from any of several places in northern France, such as Nogent-sur-Oise, named with Latin Novientum, apparently an altered form of a Gaulish name meaning ‘new settlement’.The Anglo-Norman family of this name is descended from Fulke de Bellesme, lord of Nogent in Normandy, who was granted large estates around Winchester after the Conquest. His great-grandson was Hugh de Nugent (died 1213), who went to Ireland with Hugh de Lacy, and was granted lands in Bracklyn, County Westmeath. The family formed itself into a clan on the Irish model, of which the chief bore the hereditary title of Uinsheadun (Irish Uinnseadún), from their original seat at Winchester. They have been Earls of Westmeath since 1621. The name is now a common one in Ireland, and has been adopted there by some who have no connection with the clan.
Boy/Male
Muslim
Sample, Model, Paragon
Boy/Male
Arabic, Muslim
Model; Example
Boy/Male
Tamil
Ayilyam | அயீலà¯à®¯à®®
Model state of india
Ayilyam | அயீலà¯à®¯à®®
Surname or Lastname
English and French
English and French : nickname for a tall person, from Old English lang, long, Old French long ‘long’, ‘tall’ (equivalent to Latin longus).Irish (Ulster (Armagh) and Munster) : reduced Anglicized form of Gaelic Ó Longáin (see Langan).Chinese : from the name of an official treasurer called Long, who lived during the reign of the model emperor Shun (2257–2205 bc). his descendants adopted this name as their surname. Additionally, a branch of the Liu clan (see Lau 1), descendants of Liu Lei, who supposedly had the ability to handle dragons, was granted the name Yu-Long (meaning roughly ‘resistor of dragons’) by the Xia emperor Kong Jia (1879–1849 bc). Some descendants later simplified Yu-Long to Long and adopted it as their surname.Chinese : there are two sources for this name. One was a place in the state of Lu in Shandong province during the Spring and Autumn period (722–481 bc). The other source is the Xiongnu nationality, a non-Han Chinese people.Chinese : variant of Lang.Cambodian : unexplained.
Girl/Female
Arabic, Muslim
Example; Model; Demo
Surname or Lastname
English and Scottish
English and Scottish : occupational name for a stonemason, Middle English, Old French mas(s)on. Compare Machen. Stonemasonry was a hugely important craft in the Middle Ages.Italian (Veneto) : from a short form of Masone.French : from a regional variant of maison ‘house’.George Mason (1725–92), the American colonial statesman who framed the VA Bill of Rights and Constitution, which was used as a model by Thomas Jefferson when drafting the Declaration of Independence, was a VA planter, fourth in descent from George Mason (?1629–?86), a royalist soldier of the English Civil War who had received land grants in VA. As well as being prominent in the affairs of VA, the family also produced the first governor of MI.
Boy/Male
Egyptian
To model.
Boy/Male
Hindu
Model state of india
Male
Japanese
(æ£å‰‡) Japanese name MASANORI means "model of justice."
Surname or Lastname
German
German : habitational name from any of several places so named, for example in Westphalia and Switzerland.German : nickname from Middle High German heiden ‘heathen’, Old High German heidano, apparently a derivative of heida ‘heath’, modeled on Latin paganus (see Pain 1). The nickname was sometimes used to refer to a Christian knight who had been on a Crusade to fight in the Holy Land.Jewish (Ashkenazic) : of uncertain origin; possibly a shortened form of any of various ornamental names formed with German Heide- ‘heath’, for example Heidenberg, Heidenkorn, Heidenkrug, Heidenwurzel.English : variant spelling of Hayden.Dutch : shortened form of vanderHeiden.
Girl/Female
Christian & English(British/American/Australian)
Model or Pattern
Girl/Female
Czech, Czechoslovakian, Danish, Finnish, German, Hebrew, Irish, Jewish, Polish
Friend; Beautiful; Model of Righteous Convert; Friendship
Surname or Lastname
English and Dutch
English and Dutch : from the medieval personal name Benedict (Latin Benedictus meaning ‘blessed’). This owed its popularity in the Middle Ages chiefly to St. Benedict of Norcia (c.480–550), who founded the Benedictine order of monks at Monte Cassino and wrote a monastic rule that formed a model for all subsequent rules. No doubt the meaning of the Latin word also contributed to its popularity as a personal name, especially in Romance countries.
NORMALIZATION MODEL
NORMALIZATION MODEL
Female
Russian
 Feminine form of Russian Nikolai, NIKA means "victor of the people." Compare with another form of Nika.
Girl/Female
Latin American Scottish Russian Spanish
Famous.
Girl/Female
Tamil
Fait, Noble, Relative
Boy/Male
Slavic
Universal ruler.
Boy/Male
Shakespearean
King Henry V' Officer in the King's army.
Girl/Female
Christian, Danish, Finnish, German, Greek, Scandinavian, Swedish
Follower of Christ; Christian Woman; Variant Form of Christine
Girl/Female
American, Arabic, Australian, Chinese, Danish, French, Greek, Hebrew, Latin, Polish, Portuguese, Swedish, Ukrainian
Night; Form of Lilac; Bluish; What Belongs to Me Belongs to God; Variant of Lillian Derived from the Flower Name Lily; Symbol of Innocence; Purity; And Beauty; Lily Flower Name; Lilac; Lilies; The Name of the Flower
Girl/Female
Tamil
Vishnumaya | விஷà¯à®£à¯à®®à®¾à®¯à®¾
Goddess Parvati
Boy/Male
Hindu
Learned
Boy/Male
Arabic, Muslim
Brilliant
NORMALIZATION MODEL
NORMALIZATION MODEL
NORMALIZATION MODEL
NORMALIZATION MODEL
NORMALIZATION MODEL
v. t.
To represent by a type, model, or symbol beforehand; to prefigure.
a.
Suitable to be taken as a model or pattern; as, a model house; a model husband.
n.
The act or art of making a model from which a work of art is to be executed; the formation of a work of art from some plastic material. Also, in painting, drawing, etc., the expression or indication of solid form.
n.
Explanation in a moral sense.
v. t.
To plan or form after a pattern; to form in model; to form a model or pattern for; to shape; to mold; to fashion; as, to model a house or a government; to model an edifice according to the plan delineated.
v. i.
To make a copy or a pattern; to design or imitate forms; as, to model in wax.
n.
The act or process of reducing to a formula; the state of being formulized.
v. t.
To model.
n.
Something intended to serve, or that may serve, as a pattern of something to be made; a material representation or embodiment of an ideal; sometimes, a drawing; a plan; as, the clay model of a sculpture; the inventor's model of a machine.
n.
Reduction to a standard or normal state.
p. pr. & vb. n.
of Model
imp. & p. p.
of Model
n.
Anything which serves, or may serve, as an example for imitation; as, a government formed on the model of the American constitution; a model of eloquence, virtue, or behavior.
n.
The act of moralizing; moral reflections or discourse.
n.
Relative dimensions, without difference in proportion of parts; size or degree of the parts or components in any complex thing, compared with other like things; especially, the relative proportion of the linear dimensions of the parts of a drawing, map, model, etc., to the dimensions of the corresponding parts of the object that is represented; as, a map on a scale of an inch to a mile.
n.
One who models; hence, a worker in plastic art.
v. t.
To represent by an image, form, model, or resemblance.
a.
Of the nature of a type; representing something by a form, model, or resemblance; emblematic; prefigurative.