# Questions tagged [normalization]

Usually "normalization" means re-expressing univariate data to make values lie within a specified range.

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### Loss function weighting in regression when the target varies orders of magnitude between groups

I have a dataset with 200 groups, and 50-300 observations per group. The target I'm trying to predict is a strictly positive financial metric, which varies 5+ orders of magnitude between groups but is ...
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### Normalising AIC to compensate for missing data?

AIC is simply penalised log-loss, and log-loss depends directly on the dataset size. To create a model from data, missing data need to be excluded first. Assuming missing data are spread across ...
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1 vote
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### When should one normalise the data and when should one standardize the data as a part of data pre-processing while building ML models?

I have seen people using both normalisation which is min-max normalization ( all values will be between 0,1) and standardize( normal distribution) the data as part of pre-processing. It's given that ...
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9 views

1 vote
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### Best way to analyse two experiments

I'm looking for help/indication on approaching a data integration problem. I have a dose-response curve that is described by a log curve. Because of measurement difficulties, the dose and response can'...
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56 views

I am trying to normalize prices based on the (median, MAD) transformation. I attach a image below describing it in comparison to the (mean, std) normalization. I have trouble underatanding if ...
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### Is the min-max rescaling or z-score normalization more appropriate when comparing data of vastly different mean, SD, and range?

I have six lists of data in Python where each list contains 23 items as follows. ...
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### Interpreting negative binomial coefficients from Yeo-Johnson-transformed independent variables

I am running a multiple negative binomial regression with some transformed independent variables. The IVs were skewed, so I performed a Yeo-Johnson power transformation on the data, and then ...
72 views

### Can I use normalization and standardization on the same dataset?

I'm working on an ML project to predict wine quality from a wine's physical characteristics. The features of my data are on vastly different scales so I've been experimenting with different ...
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1 vote
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### What's the proper way to analyze data from an experiment where participants perform different tasks?

I've recently conducted an experiment on my university where participants had to perform various tasks using two different virtual reality interaction methods (each participant performed all tasks ...
1 vote
27 views

### Regularize variables for Johansen coinegration

I am looking into applying the Johansen cointegration procedure to variables of very different scales, going from units to tens of thousands. I use log(prices) but the scale difference is still very ...
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### Prediction with normalization of features

I am working with a time series data (date column and a value column) and I have extracted date features(weekday, weekend etc) and rolling means or the prediction. For features to be given equal ...
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### Hello, I am doing a machine learning assesment project in R where I have to perform multiple linear regression and write report on all my steps

So I did some data exploratory and found that the range of my features are variable, like some columns have range between 1 to 5, while other columns like 'square_feet' has range of 500 to 2000. In ...
34 views

### Justification for normalization in a ratio scale data

Without loss of generality, I asked a group of participants $X=\{x_1,x_2,\ldots ,x_m\}$ to give scores in a $L$-point ratio scale $0,\ldots,l$ to different items $C=\{c_1,c_2,\ldots ,c_n\}$ based on ...
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### Help creating a single score using normalization

I'm attempting to create a single performance score based on key performance indicators that have been identified for a brand. The three specific data sets are: social net sentiment, search interest ...
1 vote
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### Intuition on normalizing to 0 mean and unit variance [duplicate]

What is the intuition, whether geometric or otherwise, to scale 1D scalar data to 0 mean and unit variance? The zero mean seems straightforward, particularly for ML algorithms, but what is the ...
61 views

### Shouldn't I do standardization when data is not normally distributed?

I am trying to scale the data prior to clustering analysis, and got a question. The goal of scaling at this point is to unify(eliminate) the unit of all input variables so that make influence of each ...
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### Why does plot between same scaled and unscaled data look different? [closed]

I am using the StandardScaler of Scikit-learn to scale my data. When plotting the data and comparing scaled with unscaled I get different results in how the plots ...
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### How do I measure goodness of fit of data transformations that standardize for variables?

I am modeling a dependent variable which has significantly different distributions when grouped by various independent variables. Consequently, it is difficult to compare previous values of the ...
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1 vote
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### how to normalize data 'with a sample range from -1 to 1 and a mean value of 0'?

I am trying to pre-process data following a statement in a paper. They said for the normalization, each dataset is normalized on a per channel basis with a sample range from -1 to 1 and a mean value ...
38 views

### How normalized, weighted composite score measaured?

How can we convert a vector of repeated measures of a variable into one value when the vector has varying length in different instances? For instance, let's assume ...
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### Sequence of pre processing methods of machine learning

I have a big dataset. It is a categorical data set. I used label encoder to change the categorical values to the integer values. I would like to find out the co relation between class attribute and ...
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1 vote
107 views

### Normalize the number of cells per patient to achieve equal contribution of patients for Wilcoxon rank sum test

I'm analyzing a single-cell RNAseq dataset where each patient has a few hundreds of sequenced cells before and after a medical intervention (blue and orange colors respectively in the graph below): I ...
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### Normalization/standardization impact on T-SNE and K-means

I have a dataset of 20K samples on 27 features that I am trying to cluster with k-means. The dataset is in its majority rather sparse, i.e. 98% of samples have a single nonzero value in one of its ...
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### How to normalise sequencing and qRT-PCR data for joint correlation analysis

We would like to analyse the correlation between cytokine (IL-6) and miRNA expression. However, we quantified the cytokine level in samples, in which the miRNA expression was quantified using either ...
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It's my understanding that if I center $y$, the intercept should be 0. However, when using glmnet, I get a non-zero intercept doing this: ...