Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [standardization]

Usually refers to "z-standardization" which is shifting and rescaling data to assure they have zero mean and unit variance. Other "standardizations" are possible, too.

Specifically, when $(x_i), i=1, \ldots, n$ is a batch of data, its mean is $m=(\sum_i x_i)/n$ and its variance is $s^2 = v=(\sum_i(x_i-m)^2)/\nu$ where $\nu$ is either $n$ or $n-1$ (choices vary with application). Standardization replaces each $x_i$ with $z_i = (x_i-m)/s$.

Do not confuse standardization with or .

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When conducting multiple regression, when should you center your predictor variables & when should you standardize them?

In some literature, I have read that a regression with multiple explanatory variables, if in different units, needed to be standardized. (Standardizing consists in subtracting the mean and dividing by the standard deviation.) In which other cases…
mathieu_r
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What's the difference between Normalization and Standardization?

At work we were discussing this as my boss has never heard of normalization. In Linear Algebra, Normalization seems to refer to the dividing of a vector by its length. And in statistics, Standardization seems to refer to the subtraction of a mean…
Chris
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Is standardization needed before fitting logistic regression?

My question is do we need to standardize the data set to make sure all variables have the same scale, between [0,1], before fitting logistic regression. The formula is: $$\frac{x_i-\min(x_i)}{\max(x_i)-\min(x_i)}$$ My data set has 2 variables,…
user1946504
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Variables are often adjusted (e.g. standardised) before making a model - when is this a good idea, and when is it a bad one?

In what circumstances would you want to, or not want to scale or standardize a variable prior to model fitting? And what are the advantages / disadvantages of scaling a variable?
Andrew
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Perform feature normalization before or within model validation?

A common good practice in Machine Learning is to do feature normalization or data standardization of the predictor variables, that's it, center the data substracting the mean and normalize it dividing by the variance (or standard deviation too). For…
SkyWalker
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Data normalization and standardization in neural networks

I am trying to predict the outcome of a complex system using neural networks (ANN's). The outcome (dependent) values range between 0 and 10,000. The different input variables have different ranges. All the variables have roughly normal…
Boris Gorelik
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How to apply standardization/normalization to train- and testset if prediction is the goal?

Do I transform all my data or folds (if CV is applied) at the same time? e.g. (allData - mean(allData)) / sd(allData) Do I transform trainset and testset separately? e.g. (trainData - mean(trainData)) / sd(trainData) (testData - mean(testData)) /…
DerTom
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whether to rescale indicator / binary / dummy predictors for LASSO

For the LASSO (and other model selecting procedures) it is crucial to rescale the predictors. The general recommendation I follow is simply to use a 0 mean, 1 standard deviation normalization for continuous variables. But what is there to do with…
László
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When and how to use standardized explanatory variables in linear regression

I have 2 simple questions about linear regression: When is it advised to standardize the explanatory variables? Once estimation is carried out with standardized values, how can one predict with new values (how one should standardize the new…
teucer
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Is standardisation before Lasso really necessary?

I have read three main reasons for standardising variables before something such as Lasso regression: 1) Interpretability of coefficients. 2) Ability to rank the coefficient importance by the relative magnitude of post-shrinkage coefficient…
Jase
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What does "normalization" mean and how to verify that a sample or a distribution is normalized?

I have a question in which it asks to verify whether if the Uniform distribution (${\rm Uniform}(a,b)$) is normalized. For one, what does it mean for any distribution to be normalized? And two, how do we go about verifying whether a distribution…
Ada
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When to normalize data in regression?

Under what circumstances should the data be normalized/standardized when building a regression model. When i asked this question to a stats major, he gave me an ambiguous answer "depends on the data". But what does that really mean? It should…
Raj
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Question about standardizing in ridge regression

Hey guys I found one or two papers which use ridge regression (for basketball data). I was always told to standardize my variables if I ran a ridge regression, but I was simply told to do this because ridge was scale variant (ridge regression wasn't…
l_davies93
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What's the difference between standardization and studentization?

Is it that in standardization variance is known while in studentization it is not known and therefore estimated? Thank you.
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Does random forest need input variables to be scaled or centered?

My input variables have different dimensions. Some variables are decimal while some are hundreds. Is it essential to center (subtract mean) or scale (divide by standard deviation) these input variables in order to make the data dimensionless when…
YQ.Wang
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