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

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10 views

real time object tracking

I have correlation value of object using mean and standard deviation, now i want to normalized that correlation value. how can get normalized correlation in terms of percentage vale?
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1answer
48 views

If I divide my data by its mean, does it still have a unit?

When dividing a timeseries by its mean value so that its mean becomes 1, does the resulting data still have a unit or is it unitless?
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23 views

UnReSolved Mean Adjust DataSet to achieve .5 Mean [duplicate]

Update So I've done some of my own work on transformational methods, and the best I can get is what I call an s transform as detailed in this workbook; however, various attempts at trying to mean ...
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2answers
51 views

Scaling a series of numbers

Suppose I have 30 numbers that vary between 0 and 1.0 and which sum to 1.0. The mean is obviously 0.033. A client wants these scaled to lie between 0 and 1.0 but to have a mean of 0.5. By the way, ...
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8 views

Normalize sequence lengths

I'm implementing a Markov Chain Model for web site access sequences. Some sequences are very lengthy and some are very short containing a single transition. Lengthy sequences generate a very low ...
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1answer
27 views

Can we run a chi squared test on a normalized function?

Hi I am fit a maxwell distribution and attempt to find the chi squared value in two cases: When the data is normalized. When the data is un-normalized. My problem is that the two ...
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10 views

Assign attributes / categories to users based on their activity / likes

I have a very practical classification problem for which I need some help. I have a database of users along with their activity / likes for a number of car models. I also have the category each of ...
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18 views

Most efficient vector construction for Dynamic Time Warping

I'm in the process of folding FastDTW into my SVM and the question now is how to best format my data (irrespective of normalization). Here's an example of what I'm attempting to do - given two 3d ...
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27 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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26 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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13 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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20 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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12 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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1answer
62 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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1answer
50 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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1answer
31 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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1answer
29 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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39 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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56 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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27 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
20 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
27 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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17 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
52 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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47 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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21 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
74 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
51 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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38 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 ...
3
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1answer
57 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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34 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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16 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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32 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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26 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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39 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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1answer
59 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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99 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
40 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
87 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
112 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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1answer
35 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
38 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
167 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
37 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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45 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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117 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 ...