A way of re-expressing data to make their values lie between 0 and 1 (or 0% and 100%).

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13 views

Order of preprocessing steps in a binary classification problem

I have these stages (ordered) for preprocessing in my binary classification problem. Dividing data based on criteria (class1 and class2 databases) Outlier ...
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15 views

Visualization - less extreme flattening of ranges

90% of the chart------------------------------------------------------------------------------| 10% of chart I am normalizing my data between 0-100 but, now seeing a flaw in visualization when (see ...
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17 views

normalizing a dataset

I have a dataset that has budget numbers for various organizations. The numbers range from less than a million to hundreds of millions. The dataset also has information about various departments in ...
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9 views

Proper “normalization” of post-test data to pre-test conditions

I'm performing an in vitro assay in which cells are treated with different combinations of two different compounds and the activity of the cells following treatment is measured. There are 3 ...
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9 views

How to access all the columns of a matrix one by one for normalizing in R [migrated]

I have a matrix which looks like this: Col1| Col2| Col3 | Col4 | Col4 | .... | | | | | .... | | | | | .... and I ...
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16 views

normalizing a proportion of poll results given unequal gender response rates

I took a poll of patients who experienced at least one misdiagnosis. I'd like to analyze the data according to gender but 75% of the responses came from Females and 25% from Males. Example: The data ...
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13 views

newbie question - regression vs composite normalised scores

Lets say I need to rank the "strength" of a bunch of objects based on a number of factors, as far as I can tell, there are two ways people seem to commonly do this : (a) calculate normalised scores ...
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7 views

Un-smoothing/scaling (help normalizing data)

The context of this is matching experimental RNA SHAPE data to theoretical models of base pairing probabilities. RNA folds back on itself, some bases pair with each other, and some bases remain ...
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51 views

Standardizing before/after/at all when using multi-class LDA for pre-processing step

If a multi-class Linear Discriminant Analysis (or I also read Multiple Discriminant Analysis sometimes) is used for dimensionality reduction (or transformation after dimensionality reduction via PCA), ...
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43 views

Normalizing Vs. Scaling

Are the concepts of normalizing and scaling of data in conflict with each other? I am adding weights to my features, I have tried normalizing the weights and it didn't make any difference in the ...
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29 views

How to : a brief intro to scaling and rescaling data ( inputs) for supervised learning algorithms

I understand the concept of scaling and that it improves results in SVM's and NN's. however I would like to find somewhere where is is explained, in easy "layman's terms" terms. of how it is done. I ...
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27 views

Scaling in SVM (why and how to , plus references)

Hi I know why feature scaling is preferred in SVM, I have two questions: 1-does anyone know of legit articles of books explaining it. I am writing my thesis and I need references. It doesnt have to be ...
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36 views

Averaging z scores when doing a “group by”

I have a dataset where each row is an hourly measurement of certain fields (columns). For each column I then add another column that is its respective z score relative to the entire population. If I ...
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41 views

How to normalize bimodal (or multimodal) distributions?

If I have multiple data series, a = [a1, a2, ... a100] ~ bimodal with mu_a1, mu_a2, sigma_a1, sigma_a2, b = [b1, b2, ... b100] ~ bimodal with mu_b1, mu_b2, sigma_b1, sigma_b2, c = [c1, c2, ... ...
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26 views

Usefulness of Z-normalization in Machine Learning

Z-normalization means rescaling the feature $X$ by subtracting the average $\mu$ and dividing by its standard deviation $\sigma$, i.e., $(X-\mu)/\sigma$. What is the usefulness of normalizing data ...
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1answer
19 views

What is the range of values that can be expected in the result of Principal Component Analysis (PCA)?

I want to normalize all of my preprocessing techniques between 0 and 1 so I want to know what the PCA range of values is so that I can apply a proper normalization to it. I applied PCA by using the ...
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1answer
23 views

Are SVD (Singular Value Decomposition) values always positive? Is there a relation between the maximum SVD value and the original data?

Assuming it's the standard SVD (no variation of it) with $A = USV^T$, would the $A$ matrix always have positive values (0 to $\infty$)? I noticed that the $U$ and $V^T$ matrices had some negative ...
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16 views

Normalization against Covariates

I have a list of parameters which correlate with 1-2 covariates that I want to control for. Following normalization, I wanted to do comparisons between groups, correlation analysis and probably use ...
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1answer
44 views

Using F-tests for variance in non-normal populations

I'm fairly new to stats, so please excuse me if this problem is hopelessly elementary or misinformed. Basically, I'm wondering if you can help me understand whether I'm using the F-Test for variance ...
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1answer
42 views

Feature Normalization/Standardization before or after Feature Selection?

Should the process of feature normalization/standardization be done before or after the feature selection process?
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19 views

Does a time-series have to be stationary before you calculate a z score or t score?

It's been a long time since basic statistics. I have a financial time-series that exhibits exponential growth. Before I standardize, do I have to make the time-series stationary? Before I ...
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1answer
64 views

Inputs to k-means are often normalized per-feature. Why not fully whiten the data instead?

We often normalize inputs to the k-means algorithm by 1) subtracting the mean on a per-feature basis and 2) dividing by the standard deviation on a per-feature basis. Some rational behind this is ...
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17 views

Normal Data Distribution (Visual tests accept and statistical test ks reject normal distribution) Need Help [duplicate]

I have four variables want to run regression while i check for data distribution i found that histogram and qq plot provide evidance of normal data distribution where as ks test is significant for all ...
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1answer
48 views

Is there a formal name for this data normalization formula?

I am using a generalized formula for normalizing one data range to another but am having difficulty finding its formal name, if it even exists (sorry if my notation is strange): $$ x_b = min_b + ...
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30 views

regression trees + scale of output variable

I am developing a regression tree model I have an output variable with a very large standard deviation, I am wondering if I need to scale/normalize this output variable as metrics such as RMSE and R^2 ...
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1answer
54 views

Difference in tf-idf values in R

I am playing around in R to find the tf-idf values. I have a set of documents like: ...
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1answer
34 views

Normalization with error in denominator

I am trying to come up with a proper way to normalize my data. Using a microscope I want to count the percentage of green cells in a population. However, only ~0.1% of all cells are green. I decided I ...
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35 views

Data normalization with preference to a number size

I understand that data normalization allows us to take data and place it on a scale of [0,1]. Currently I'm working through a machine learning book and the author talks about normalizing data with ...
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33 views

standardising sub-data sets, such that the whole dataset is standardised

Consider a data set $X$ made up of smaller subsets: $X=A \cup B \cup C$, with $A,B,C$ disjoint data sets. Eg: $A=\{1.0, -1.0, 0\}$, $B=\{5.0, -7.0, 2.0\}$, $C=\{1.5, -5.0, 8.0\}$ Is is possible ...
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15 views

How to create a score that gives same weight to N variables using different scales?

I'm analyzing a website, we have three variables Pageviews, Minutes spent on site and Entrances and want to produce a score that gives equal weight to each of them. At first I was simply going to ...
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29 views

Normalizing weekly sales fluctuations in the overall market

I have a rudimentary question regarding how to "normalize" a set of time series data, and would appreciate your thoughts. To make it very simple, the hypothetical situation is as follows: Suppose we ...
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1answer
21 views

Accelerometer normalization

I'm working with data from different accelerometer hardware. Each hardware has a different maximum range, different resolution at which data changes, and different minimum delay after which a new ...
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32 views

Normalize by expected value

If I have an underlying distribution of expected values, how do I normalize my observed values by this distribution? Here is an example: I am testing for a deviation from 50:50 (my Null ...
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55 views

De normalize predicted value

Alright so i have found this really good answer on how to normalize my data. I implemented @user25658 's code into my own project successfully, trained a linear model and used it to make a ...
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98 views

New Systematic Quantile Normalization

I think I've developed a systematic quantile normalization technique. I did this with music but I think it can also be done with light and other frequency based information. The algorithm is as ...
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1answer
38 views

How to analyse data from different subjects?

DESIGN: I have 4 laboratory mice (= 4 subjects). My factor is a condition with 5 levels ...
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1answer
81 views

histogram normalised to area 1

i have a histogram with the y-axis showing the proportion in percentage. That makes sense to me but now i have read that histograms can be normalized with the result that the area of the rectangles is ...
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1answer
85 views

Too big (?) histogram values when using normed histo options in SciPy and matplotlib

I have been trying to create a normed histogram using either SciPy or matplotlib (or anything for Python). When I create my histogram with 'normed' option disabled, it looks like below (this example ...
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34 views

When to scale/normalize for supervised learning algorithms?

I'm trying to understand which supervised learning algorithms require normalization/scaling of features. It appears that when an algorithm works by calculating the conditional probability (Naive ...
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1answer
35 views

Normalization Factor divide or multiply

If I want to normalize some data using a median normalization or trimmed mean normalization, do I multiply or divide my data by the normalization factors? Does it matter?
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2answers
143 views

Normalization of dummy variables

My data consists of several continuous measurements and some dummy variables representing the years the measurements have been made. Now, I want to learn a neural network with the data. Therefore, I ...
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1answer
34 views

how to transform data of two experimental groups? one is positively skewed and one is negatively..

I have two experimental groups. Then I test their normality respectively. Result shows that one is positively skewed and the other is negatively skewed. In this case, how should I do the data ...
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39 views

Normalizing depth data

I have some Kinect data of somebody standing (reasonably) still and performing sets of punches. I am given it in the format of an x,y,z co-ordinate for each joint of which they are 20, so I have 60 ...
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2answers
86 views

How to transform negative data to be homoscedastic

I have a bunch of data that's both positive and negative. Its calculated from the residuals of an ANOVA (i.e. specific leaf area calculated as the residuals of an ANOVA of leaf area with leaf blade ...
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1answer
23 views

Normalization for pattern classification?

I'm working off my first independent project for some pattern classification. I'm utilizing some datasets from UCI machine learning, but am not sure on how to start with data normalization. The data ...
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1answer
87 views

SVM data normalization… what about classifying new (training) data?

I've got a big doubt about SVM classification task (and more in general classification task), about data normalization. Let's suppose I've a SVM trained with normalized data, and new data to classify. ...
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18 views

Pre-stimulus baseline removal in R

I have the following scenario: trials were conducted where participants were exposed to multiple stimuli during the course of a trial a specific physiological response was continuously recorded ...
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45 views

Scaling/Normalisation or Standardization

I'm working on SVM and ANN classification tools. In order to improve the classification accuracy, I want to know the best or the recommended data-preprocessing, is it scaling/normalisation or ...
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20 views

Normalization on frequently updated dataset

There are some normalization types like rescaling, standart score or modified standart score. I can apply these algorithms to large dataset. If the dataset that i am working on getting frequently ...
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24 views

The number of coin tosses needed if the proportion of heads is to lie within 0.05 of p with probability at least 0.9?

There's a question I'm not really sure if I did it right or even understand what its trying to say. There is a coin which produces heads with an unknown probability $p$. How many times should we ...