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In statistics, an additive model (AM) is a nonparametric regression method. It was suggested by Jerome H. Friedman and Werner Stuetzle (1981) and is an essential part of the ACE algorithm. The AM uses a one-dimensional smoother to build a restricted class of nonparametric regression models. Because of this, it is less affected by the curse of dimensionality than e.g. a p-dimensional smoother. Furthermore, the AM is more flexible than a standard linear model, while being more interpretable than a general regression surface at the cost of approximation errors. Problems with AM, like many other machine learning methods, include model selection, overfitting, and multicollinearity.

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rdf:type	software
rdfs:label	Additives Modell (de) Additive model (en)
rdfs:comment	In der Statistik ist ein additives Modell (AM) ein nichtparametrisches Regressionsmodell. Es wurde durch und Werner Stuetzle (1981) vorgeschlagen. Das additive Modell verwendet einen eindimensionalen Glätter, um eine eingeschränkte Klasse von nichtparametrischen Regressionsmodellen zu bilden. Daher ist das Modell weniger durch den Fluch der Dimensionalität betroffen als beispielsweise ein p-dimensionaler Glätter. Das AM ist flexibler als gewöhnliche lineare Regressionsmodelle. Probleme, die beim additiven Modell auftreten können, sind Überanpassung und Multikollinearität. (de) In statistics, an additive model (AM) is a nonparametric regression method. It was suggested by Jerome H. Friedman and Werner Stuetzle (1981) and is an essential part of the ACE algorithm. The AM uses a one-dimensional smoother to build a restricted class of nonparametric regression models. Because of this, it is less affected by the curse of dimensionality than e.g. a p-dimensional smoother. Furthermore, the AM is more flexible than a standard linear model, while being more interpretable than a general regression surface at the cost of approximation errors. Problems with AM, like many other machine learning methods, include model selection, overfitting, and multicollinearity. (en)
dcterms:subject	Nonparametric regression Regression models
Wikipage page ID	20964272 (xsd:integer)
Wikipage revision ID	1078143924 (xsd:integer)
Link from a Wikipage to another Wikipage	Robert Tibshirani Curse of dimensionality Generalized additive model Projection pursuit regression Model selection Smooth function Statistical unit Statistics Median polish Nonparametric regression Regression models Trevor Hastie Data Linear regression Alternating conditional expectations Journal of the American Statistical Association Nonparametric regression Backfitting algorithm Jerome H. Friedman Generalized additive model for location, scale, and shape Multicollinearity Smoothing Overfitting Friedman, J.H. Projection Pursuit
sameAs	Additive model Additive model Additive model Additive model Additive model
dbp:wikiPageUsesTemplate	dbt:Doi dbt:Reflist
has abstract	In der Statistik ist ein additives Modell (AM) ein nichtparametrisches Regressionsmodell. Es wurde durch und Werner Stuetzle (1981) vorgeschlagen. Das additive Modell verwendet einen eindimensionalen Glätter, um eine eingeschränkte Klasse von nichtparametrischen Regressionsmodellen zu bilden. Daher ist das Modell weniger durch den Fluch der Dimensionalität betroffen als beispielsweise ein p-dimensionaler Glätter. Das AM ist flexibler als gewöhnliche lineare Regressionsmodelle. Probleme, die beim additiven Modell auftreten können, sind Überanpassung und Multikollinearität. (de) In statistics, an additive model (AM) is a nonparametric regression method. It was suggested by Jerome H. Friedman and Werner Stuetzle (1981) and is an essential part of the ACE algorithm. The AM uses a one-dimensional smoother to build a restricted class of nonparametric regression models. Because of this, it is less affected by the curse of dimensionality than e.g. a p-dimensional smoother. Furthermore, the AM is more flexible than a standard linear model, while being more interpretable than a general regression surface at the cost of approximation errors. Problems with AM, like many other machine learning methods, include model selection, overfitting, and multicollinearity. (en)
gold:hypernym	Method
prov:wasDerivedFrom	wikipedia-en:Additive_model?oldid=1078143924&ns=0
page length (characters) of wiki page	2612 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Additive_model
is Link from a Wikipage to another Wikipage of	Scatterplot smoothing Decomposition of time series Interaction (statistics) Generalized additive model Gene–environment interaction Seasonal adjustment Projection pursuit regression Functional data analysis Functional regression Stephen Grossberg Alternating conditional expectations Additive Additive Model Tukey's test of additivity Group-contribution method Huber loss Seasonality List of statistics articles Additive models
is Wikipage redirect of	Additive Model Additive models
is Wikipage disambiguates of	Additive
is foaf:primaryTopic of	wikipedia-en:Additive_model

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