A way of re-expressing data to make their values lie within a specified range.

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4 views

Normalize a dataset (4d, two distance types)

I have a 4d dataset. The first two dimensions consist of latitude and longitude coordinates. Hence they will utilize the orthodromic distance. Latitudes range from -90 to 90. Longitudes range from ...
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7 views

Using alternative normalization method in DESeq analysis of gene enrichment

I'm using DESeq to identify differentially expressed genes in a next-gen sequencing dataset. (DESeq: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3218662/). In my experiment, the normalization of read ...
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23 views

Scale and normalization of dates

It's common to normalize the different vars before applying some kind of supervised/unsupervised learning. Which algorithm do you use with the dates? You use the day of year (1, 200, 300) and perform ...
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6 views

Performance metrics, prioritizing based on impact

I apologize in advance for the poorly worded question. If anyone has any suggestions, please advise. Also, help with tagging appropriately would be appreciated. I'm collecting performance metrics ...
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29 views

Importance and effect of mean normalization and feature scaling for PCA [duplicate]

What is the importance of mean normalization and feature scaling as a pre-processing step for principal component analysis (PCA)? What will be the result if I don't follow these pre-processing steps ...
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1answer
37 views

Why normalize input variables in NN?

I'm reading the 'Efficient Backprop' paper and it's mentioned that the reason to have a zero mean for the input variables is because otherwise the eigenvalue (for the hessian I think) will be very ...
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7 views

Rank-sensitive distance estimator

So, for reasons that are a little complex to get into I find myself dealing with some improperly-normalized feature vectors. This means that when I try a traditional distance metric (euclidean, ...
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11 views

Normalize data points against an expected value

I have set of data points(y coordinates) representing peak points in an graph. Each data set consist of 4 groups and each group contains list of data points representing y coordinates in graph. I want ...
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25 views

What's the difference in effect of the two ways to normalize data?

When I first started learning applied statistics, I was always taught that normalizing data for use in models was to do the following: $ \frac{x - \bar{x}}{std(x)} $ This scales your data to 0-mean, ...
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9 views

Why do we need to normalize data into interval [0,1] in subtractive clustering? How about Z-score?

I read that we need to normalize data into interval [0,1] in subtractive clustering. Is there any difference if we standardize data into Z-score or other interval instead of normalize it into [0,1]?
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33 views

Choosing contrast coding in R

I am working on a data set with categorical variables. To apply ANN, I want to apply contrast coding to those variables. But how do I choose between coding functions in R (sum, helmert, treatment ...
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18 views

Avg ST DEV vs St. Dev of Avgs

I have monthly sales figures, and have a column with the avg monthly sales figure. I also have a column for the st dev of each member's monthly sales figures. I want to standardize these values, and ...
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27 views

Normalization of distributions

I am measuring intensities of structures in biological tissues, which gives a series of values for each sample. There is high variability between values for each samples from unknown procedural ...
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1answer
20 views

How does normalizing the response affect likelihood?

I have a vector of experiment outcomes, $Q$, and I assume that $Q_i$ are generated by a Gaussian distribution, i.i.d., such that the likelihood is the standard $$\mathcal{L}(q_1, ..., q_n) = ...
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1answer
32 views

What is the difference between data normalization and feature extraction in deep learning?

I am learning about the multi-modal deep learning models and the papers I am reading are very confusing on one point in the process: "feature extraction" and "data normalization" seem to be used ...
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17 views

ANOVA on a normally and a log-normally distributed variable: what to transform?

For an analysis of variance the residuals (but not the data?) have to be normally distributed. So, I have two variables, one is normally distributed, one is log-normally distributed, and their ...
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20 views

Result different after normalisation of the dependent variable

Consider following two regressions: in case A, I didn't transform dependent variable and in case B, I normalize the dependent variable to lie between 0 and 1. I was expecting the same output, but I ...
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18 views

Normalization/Multiple Regression Question

I work in cell culture and normally don't have to use anything more than T-tests, but this project has me stumped... The study design: 1 control treatment and 7 experimental treatments with one ...
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42 views

Normalisation before and after PCA

Is it valid to normalise a dataset, reduce dimensionality with PCA and then to normalise the reduced dimension data? Assuming this is performed on training data, should the same PCA coefficients be ...
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28 views

TMM-normalization of RNA-seq data in R language using edgeR package

My data is in a numeric matrix of RNA-seq data from Illumina 2000 platform (with proper alignment and other preprocessing done), where columns represent subjects, and rows represent raw expression ...
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1answer
92 views

Why is the 'age squared' variable divided by 100 or 1000?

I am considering the first fifteen waves of the British Household Panel Survey data. I wished to know the intuition behind using age squared/1000 as one of the variables in the published papers. How ...
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1answer
14 views

Do I have to normalise the data for PERMANOVA?

Why do I have to normalise my dataset to do a PERMANOVA? What is the difference between Euclidean distance and Bray-Curtis similarity? Which is the most suitable for CPUE (abundance) data?
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17 views

Should data be centered+scaled before applying t-SNE?

Some of my data's features have large values, while other features have much smaller values. Is it necessary to center+scale data before applying t-SNE to prevent bias towards the larger values? I ...
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3answers
21 views

Is there a min max normalization function with the middle weighted towards 1?

So the standard min max is $$\ \frac{x - \min(x)}{ \max(x) - \min(x)}$$ or something like that. Given a range like 0 to 500 I would like 250 to normalize to 1, 0 and 500 to 0. What is the proper way ...
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8 views

Score-normalization in speaker verification, how to choose the dataset?

I am now building a speaker verification system and want to use some score normalization techniques, i.e. T-norm and Z-norm. However I met some questions. T-norm means that I should test every ...
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2answers
48 views

Confidence interval of ratio estimator

As an example, consider a program that executes on two computers, A and B. Measuring the execution time of 3 executions each shows the following results: System A: 10s, 10s, 4s System B: 8s, 8s, 2s ...
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2answers
45 views

What are some ways to normalize variables to compare standard deviations?

I have a list of time-series variables which are all in different scales. The variables are not normally distributed and some values are negative. What are some ways to normalize these variables so ...
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14 views

Inversely proportional version of a nearest-neighbour results vector - how?

Short version: Given an input vector D of n values, what are the different methods that one can use to return a vector W such that each value in W is in inverse proportion to the magnitudes of the ...
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1answer
30 views

Normalization of a 360-degree feedback evaluation

First of, I'm not a data scientist or anything like that so there will be a lot of hand waving (sorry about that), I just hope to get the gist across. At my company we're doing a 360-degree feedback ...
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28 views

What is the name of this procedure?

Frequently, normalization means subtracting the mean and dividing by SD. What if one standardizes the data by subtracting the median and dividing by interquartile range? Does that procedure have a ...
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10 views

Comparing conversion rate across differing group sizes

I'm trying to work out a formula for determining the normalised? conversion rate for a staff member - Converting traffic into a sale. This is to determine the most successful staff at conversion in ...
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58 views

Normalization or standardization for distances in a Q-mode cluster and principal components analyses

I want to run a cluster analysis and a PCA between some sites to classify them in terms of their multivariate dissimilarity. This is a Q-mode analysis. I am working on a data matrix made of sites in ...
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39 views

Kruskal-Wallis to compare different distributions - need to normalize due to different proportions?

I have a population of children with different genotypes, let's say genotype A, B and C. However, the proportions are different per group, for instance 60 children have genotype A, 50 genotype B and ...
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30 views

Is it possible (and if yes how) to retain a sparse matrix after normalization?

I was wondering whether given a sparse matrix it is possible to retain a sparse matrix after removing certain global effects. Let me demonstrate the following: Given a data set $X$ with dimensions $m ...
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36 views

Normalize estimated probabilities from two logistic regression models

I have built two logistic regression models predicting the probability of purchase of two products. (Product A and Product B) For every customers, I want to choose the product that has the higher ...
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44 views

Does feature size affect polynomial regression?

(I'm still trying to learn all this, sorry for any wrong terms or mistakes I might have made in this question) By feature size, I mean the value of the numbers. For example, let's say I have input ...
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22 views

Normalizing test scores — public health inspections across diverse jurisdictions

I'm building a system to put the world's restaurant health scores online. I'm implementing a data standard which only requires the scores to be 0–100, 100=maximum. That was easy. My current problem ...
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1answer
513 views

Feature scaling and mean normalization

I'm taking Andrew Ng's machine learning course and was unable to get the answer to this question correct after several attempts. Kindly help solve this, though I've passed through the level. ...
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1answer
48 views

What is the best data transformation for absolute zero inflated distributions?

I have 3 variables with the following distributions: What is the most appropriate transformation to make them as normally distributed as possible? This data is absolute zero inflated.
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1answer
20 views

Normalising extreme items within datasets

I have a a dataset where each item is a % above or below 100% (taking an individual item, dividing by the mean). In order to produce a rank I weighted each item by a % (summing to 100%) to provide a ...
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1answer
88 views

Bayes theorem: normalisation denominator and likelihood

I have been racking my brains trying to understand Bayes theorem. So, the way I have understood is that the likelihood is the probability of observing the particular outcome given a set of parameter ...
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1answer
70 views

How to normalize mixed continuous/discrete features for DNN?

I have had some success training my deep neural network (with ReLU hidden units) by first normalizing the features of my data set to zero-mean-unit-variance. Each sample of my data set has 600+ ...
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36 views

For normalized X and Y, how can the slope be equal in lm(Y~X) and lm(X~Y)

Lets consider normalized variables X and Y. Slope of a lm(Y~X) is Cor(Y,X)*sd(Y)/sd(X) and for ...
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3answers
110 views

Andrew Ng scaling and normalizing expression

I'm involved in the design of a recommender system and I'm using a mixture expression of z-score and min-max scaling for scaling and normalizing data: $X_{norm} = \frac{X - \mu}{X_{max} - X_{min}}$ ...
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2answers
117 views

LASSO - normalization of response variable needed?

I wonder whether the response variable needs to be normalized before LASSO estimation (I am using the lars package in R to perform LASSO estimation). My guess is that only right-hand side variables ...
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1answer
125 views

How do you classify based on percentile ranking when most scores are the same?

I am dealing with a simple dataset of test scores. It was an easy test -- 98 out of 100 persons got a perfect score. 1 person got a 2% and one person got a 3%. Here's what it looks like in ...
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33 views

Should I normalize my variables for a descriptive logistic regression?

I'm running a logistic regression in order to descriptively analyze the relationship between my independent and dependent variables. As I understand it, it's not mathematically necessary to normalize ...
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26 views

Weather analysis | company sales

I'm writing a python code that reads in a csv file of rain in inches for a given zip code and creates a normal distribution from the data. Ultimately, I want to be able to create some score for the ...
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44 views

Normalize time series data - Wikipedia article counts

I have: 3 wikipedia article access counts (weekly) (A-B-C) Ground truth data (weekly) Total wikipedia english article traffic counts (weekly) My purpose is, build a multiple linear regression ...
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1answer
38 views

Should I normalize the data (capital stock series) after deflating it with whole price index? [closed]

I am working on across industries. I want to know that after deflation capital stock of large scale industries with whole sale price index, Is there need of normalizing the data series?