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.
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normalization in clustering
I am working on a project where I aim to cluster provinces according to their exposure to river floods. Currently, I am considering the following indicators:
Total number of flood events / total ...
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Meaning of “standardized random variable” in multiple choice question
I would like to clarify the meaning of this question.
If Z is a standardized random variable, which of the following
statements is correct?
A) Its distribution is always Normal.
B) We always have E(Z²...
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Should I standardize or only center "Age" in an ordinal semiparametric regression model?
I am using Ordinal Semiparametric Regression (Frank Harrell's rms package) to model overall survival in patients with brain tumor. I am thinking of centering the Age covariate, because I want Age = 0 ...
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Standardizing effectsizes in a two-level logistic mixed model with highly unbalanced clusters: advisable? How to compare effect sizes?
I’m fitting a two-level logistic mixed model with a random intercept and only level-1 predictors. The data are highly unbalanced across clusters: 266 observations in 25 clusters with sizes like:
...
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Standardization of regression coefficients and standard errors with different outcome variables
With reference to below links, I would like to confirm the following:
When the outcome variable is continuous, and is scaled (assume linear model),
When the outcome variable is binary (assume ...
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Standardization after normalising the entire dataset
I am using SVR regression for that i have imported the dataset (which has already been normalized between 0 to 1 and it is a panel data) so while running the regression model i again undertook ...
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Does standardization of feature vectors in OLS regression change the meaning of the regression coefficients?
I have the ordinary least squares problem
$$
\boldsymbol{\beta}^* = \text{argmin}_{\boldsymbol{\beta}} \| \boldsymbol{X}\boldsymbol{\beta} - \boldsymbol{y}\|^2_2, \quad \text{Problem}~(1)
$$
with $\...
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How do I go about refining my ARX model in R
I face a few issues where im trying to predict my dependent variable Y. I have 6 different independent external variables with one of them being lag(1) of the dependent variable Y. I differenced all ...
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Standardizing data in Bayesian optimization
I am implementing a very basic Bayesian optimization algorithm in Matlab. It is generally recommended to standardize both the inputs (sampling points) and the outputs (black-box objective function ...
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Is the arithmetic mean appropriate when feature scaling rates?
Certain machine learning algorithms perform better when the features of the dataset have been scaled. In particular, feature standardization (subtracting the mean and dividing by the standard ...
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Standardization of Variables Across Different Analyses
Standardization of Variables
I'm conducting a study for my B.S.c. in psychology and need advice about standardizing variables for my analyses. My variables are Optimism, Stress and 4 separate ...
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How should I input and output feature and target timeseries to timeseries transformer
I am trying out PatchTST timeseries transformer (paper, code) on a timeseries data that I have. The way PatchTST handles data is as follows:
Note that on line 78-79, the repo does following:
...
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At what stage of the species distribution modelling to standardize variables and check for collinearity
I try to model the distribution (ecological niche) of a species using a generalized linear model (glm() in R) based on several climatic variables and then apply the ...
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Change in data distribution after applying scale() in R
I have a question about changes in distribution after applying scale() in R. If my whole procedure is false, I will happily welcome recommendations, corrections, ...
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Comparing logistic regression coefficients
I have data representing a population of individuals and a binary outcome of interest. The covariates themselves are often probabilities. For example, covariates 1 through 5 are an estimate of the ...
