Questions tagged [standardized]

Shifting and rescaling data to assure zero mean and unit variance.

Overview

Specifically, when xi, i =1,..., n is a batch of data, its mean is:

m=∑xi/n

and its variance is:

s2 = ∑(xi−m)2)/ν

where,

v is either n or n-1 (choices vary with application).

Standardization replaces each xi with zi = (xi-m)/s. Do not confuse standardization with normalization.


Tag usage

Questions on tag should be about implementation and programming problems, not about the statistical or theoretical properties of the technique. Consider whether your question might be better suited to Cross Validated, the StackExchange site for statistics, machine learning and data analysis.

145 questions
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add t score to existing data set in sas

How do I add a new variable with a score in an existing dataset in SAS? proc standard data=orig out=age_t mean=50 std=10; var age ; run; I want to create a new variable age_t in the original dataset with the t score for every observation
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correlation between survey response and spend

I am currently working on a problem in which I have survey response basis a survey conducted by a market research agency. The survey measured perception of coverage about the services of the product. Scale of survey: 0-100. Sample size 4K. The task…
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How to standardize matrix row-wise (axis=1)?

For a two-dimensional array, I'm trying to make a standardize-function, which should work row-wise and column-wise. I'm not sure what to do when an argument is given with axis=1 (row-wise). def standardize(x, axis=None): if axis == 0: return (x…
lvdp
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How to get standardized fitted values

I know how to get fitted values in r fitted.values(object) However I want to get standardized fitted values. I get standardized coefficients using "lm.beta" package. object1<-lm.beta(lm_object) After that I use fitted.values(object1) But I…
yuri jung
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CNN : Data standardization?

I'm working on a neural network to predict if an event is a neutrino or not. Each input x is a matrix : (3, 5484), three different measures, 5484 sensors. So I should normalize the input for the network to work properly but I have doubts about it,…
Gericault
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R knncat Error in 1:knots.vec[num.ctr]

Apologies if this is elsewhere (and if my question is done poorly - this is my first post). I have searched for days and solved all my other errors, but I keep getting this one: "Error in 1:knots.vec[num.ctr] : NA/NaN argument". I am trying to…
JHawkins
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Standardize data using monthly mean and sd

I have a dataset for 50 years (which are daily values) in the following form: Date Var1 Var2 Var3 Var4 Var5 Var6 1994-01-01 2.2 0.1 98 0 7.5 3.6 1994-01-02 4.1 3.2 70 0 2.6 5.2 1994-01-03 10.7 3.3…
Pulsar_534511
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Linear regression: Prediction issue when data is standardized

I'm working on auto-mpg dataset and I try to predict some values but I've faced this problem: before using linear_regression function of sickit learn, I standardized my data using preprocessing.scale But after that when I try to predict a value but…
aferjani
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Range standardize a complete matrix R

I'm working with pairwise distances in the format of a hollow matrix of 45 rows and 45 columns in which the upper and lower triangles are mirrored. I need to range standardize my entire matrix so that all values lie between 0 and 1. I've tried it…
Anna
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What is "standardize" in "h2o.deeplearning" options?

Manual says "Logical. If enabled, automatically standardize the data. If disabled, the user must provide properly scaled input data." I tried learning with iris data. R source code library(h2o) h2o.init() xx <- data.frame(c(1:10), c(1:10) * 10,…
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Optimization of the generation of a standardized vector

I need to generate many (100k order) random vectors of variable sizes such that: sum(v_i)=0 and sum(v_i^2)=1 sum up to zero and the sum of the squares is one, for each vector. This is the code I write: c1 <- rnorm(ki[i]) c1 <- c1-mean(c1) e1 <-…
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Standardize and rescale each column of every element in a list

I have a list of 5 dataframes like so: mydf <- data.frame(x=c(1:5), y=c(21:25),z=rnorm(1:5), p=rnorm(2:6), f=rnorm(3:7)) mylist <- rep(list(mydf),5) names(mylist) <-c("2006-01-01","2006-01-02","2006-01-03","2006-01-04","2006-01-05") I also have…
Alex Bădoi
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Applying z-score (zero mean, unit std) before scaling to [0,1]?

I'm currently using neural network for classification of a dataset. Of course before doing classification either the data points or the features should be normalized. The toolbox which I'm using for neural network requires all values to be in range…
machinery
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Standardization/preprocessing for 4-dimensional array

I'd like to standardize my data to zero mean and std = 1. The shape of my data is 28783x4x24x7, and it can thought of as 28783 images with 4 channels and dimensions 24x7. The channels need to be standardized. How do I standardize while specifying…
pir
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Standardized coefficients for lmer with accuracy scores

Apologies if I'm making any silly errors, I'm pretty new to R. I have been searching for the answer to my question, but haven't got very far! I need to report standardized coefficients for the predictors in my model. I think I have figured out how…
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