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

learn more… | top users | synonyms (1)

0
votes
0answers
6 views

Input normalization effect on Polynomial regression

Here there is a good explanation proving that column normalization does not affect linear regression. But I need to know if this is the same in polynomial regression as well. Thanks in advance,
0
votes
0answers
15 views

Tsallis and Renyi Normalized Entropy

I'm working with Shannon, Tsallis and Renyi entropies. I need to normalized these entropies for comparison purposes. In Shannon's entropy you need only to divide by the log of the number of bins. ...
1
vote
0answers
34 views

High variability in data set, how to normalize? [on hold]

For my research I'm doing FACS analysis on neutrophils isolated from venous blood. The blood is taken from different individuals each day so there is high variation in the results, resulting in a high ...
0
votes
0answers
3 views

removing batch effect when combing patient's data into a large cohort

I have some clinical data quantifying severity of disease for patients from 3 different hospitals. Basically, the patient severity vector for each hospital looks like below: ...
0
votes
0answers
10 views

How to normalize scoring to eliminate bias?

Background: I'm writing an app to allow multiple people to rate an object on a scale of 1-10. There are a few hundred objects to be rated, so I'd like to allow the reviewers to review what they can, ...
0
votes
0answers
17 views

what's your process for normalizing data?

I have a time series data set that I want to put through a simple linear regression. Besides guessing, what stat tests or processes can I use to normalize outliers?
2
votes
1answer
65 views

two-sample KS test: data becomes significantly different after normalization

I'm currently working on a data set with two sets of samples. The csv file of the data could be found here. I would like to use KS test to see if these two sets of samples are from different ...
2
votes
0answers
20 views

Normalizing regressors in logistic space

I have a bunch of sklearn sgd models that have beta coefficients in the logistic space. I want to see if these models cluster ...
1
vote
2answers
46 views

How to normalize data without an edge

Is there some calculation method which normalizes data (numbers) if I don't have minimum and maximum edge? Only one I know is: y = (x - min-x) / (max-x - min-x). But as I said I don't have an edge ...
1
vote
0answers
19 views

Time series comparisons: early detection of mismatching series after n points for efficiency

I am doing time series comparisons. I have a set of values (my query set Q) that I need to compare against many other reference sets (R), each of which contains the same number of values as my query ...
0
votes
0answers
7 views

continuous norming

I am said to apply continious norming to my data (test scores testing children). I have not found any freely available information about this process. I have found out that: 1) norming is based on ...
1
vote
1answer
32 views

Fix dominant columns/rows in symmetric data matrix?

I have a symmetric data matrix $A$, giving co-occurrence of events. That is, $A_{ij}$ is the frequency of occurrence of $i,j$ together. The diagonal elements of $A$ are unknown/indeterminate. I am ...
3
votes
1answer
33 views

Is there a way to characterize the position of a point in a distribution that takes higher moments into account?

When summarizing a location in a distribution, we can take the mean into account by simply calculating $x-\mu$. We can take the standard deviation into account by calculating a Z score ...
1
vote
0answers
18 views

How to normalize by the covariance matrix? [duplicate]

I am trying to understand an image processing research paper [1] that calls for normalizing a distance between an object's center point and the center of a cluster of points by the covariance matrix ...
0
votes
1answer
20 views

Normalization Interval variable [duplicate]

I have to perform a regression. My data set is composed of 12 independent(ration) variables and 1 dependent(interval) variable. After having performed a Normality test(kolmogorov-Smirnov) it resulted ...
1
vote
0answers
45 views

Data normalization for a recommender

this question is a copy from DataScience forum. I do hope I will get much more information and help here. At the moment I am doing some data experiments with the Graphlab toolkit. First of all, I ...
0
votes
0answers
36 views

When do we have to standardize/normalize data?

I have to perform an independent group t-test and have unequal variances. From what I understand, the solution is to transform the data. To transform it, do I standardize it? Or simple use log10 to ...
1
vote
0answers
26 views

How to normalize data in close range 0.95-1.05 to scale between 0.9 and 1? [closed]

everybody, I have a problem: I have data in close range (0.95 to 1.05 or -0.05 to to 0.05), but these values (presented as percentage in the end) can not be presented as negative numbers nor with ...
0
votes
1answer
55 views

Normalize variables for calculation of correlation coefficient

I have two vectors (arrays) of values. One vector represents a variable whose values are between 0 and 1 (ratio-type variable). The other vector represents a variable whose values are continuous float ...
0
votes
0answers
15 views

Normalisation formula applicable to one or more data items

I've created a recurrent neural network, to which normalised values are passed as inputs. The normalization formula is: $$\tilde{x_{i}} = \frac{1}{1+exp(-\frac{x_i-\bar{x}}{\sigma})},$$ where ...
0
votes
0answers
39 views

How to determine a data transformation factor

I'm working on transforming one set of data to another based on a certain variable (length). Here's how the actual problem is like: ...
0
votes
0answers
26 views

Normalization in case of clustering

Can normalization in this form be used (x−μ)/σ and should it be used in case of clustering? I have parameters on different scales and since I'm calculating the distances I need to perform feature ...
0
votes
1answer
26 views

Normalization problems - how to normalize in case of set of points while new points arriving

I'm having a procedure in which I perform clustering, and later, for each new example I test if that example belongs to some of existing clusters, by calculating distance to existing centroids. To ...
1
vote
0answers
56 views

How to normalize the data to [0, 1] in R with data similar to χ²-distribution without shrinking lower values too much?

I want to normalize the data to [0,1], but the distribution of this array is quite not regular, having large quantity of low values and small quantity of large values, almost 80% values of data are in ...
1
vote
1answer
35 views

Noise removal from a dataset with a know distribution

If I have a dataset where it's points are drawn from a known distribution(For example a normal distribution) due to some noise the histogram doesn't reflect such a behavior (not necessarily skewed) ...
2
votes
2answers
49 views

Why do we whiten the data before running ICA?

Why do we usually pre-whiten the data before doing independent components analysis (ICA), like making all eigenvalues equal? Doesn't that take away some information regarding the data?
0
votes
0answers
16 views

r-pnn, normalization and different distance measures for each variable

Since pnn is a NN that uses a Radial kernel to classify data, I think the distance measure is key and, in consequence, the normalization of the data. Am I right? How does pnn package calculate the ...
0
votes
1answer
61 views

When normalization is counter-productive [duplicate]

Could you give me general examples of when normalization is not used properly and affects badly the classification accuracy, or when it is not needed?
0
votes
0answers
11 views

System failure data - normalize data when there is more data available for that system

Suppose I have the following data from 6 systems. The number of Type A systems is 2 in 6 so 1/3. There are 2/3 of B systems. In the 6 systems there were 40 failures in total. ...
4
votes
3answers
268 views

When should I apply feature scaling for my data

I started a discussion with a collague of mine and we started to wonder, when should one apply feature normalization / scaling to the data? Lets say that we have a set of features with some of the ...
0
votes
0answers
19 views

Which type of feature scaling to use [duplicate]

I've been writing some simple machine learning algorithms and looking at time-series data. In doing so, I have come across the use of feature scaling: rescaling and standardizing as they are referred ...
0
votes
1answer
43 views

Question in Artificial neural network normalization

I wish to normalize inputs parameters into [0 - 1] and fit into a neural network for training. I have done a simple normalization method - MinMax Question 1: if my inputs have negative values, do i ...
1
vote
1answer
39 views

Cumulative standard deviation of variables with different distribution

Suppose we have a set of basketball players, each of which have 9 associated performance categories. Each of these categories has a different distribution. I want to find a good way to represent how ...
2
votes
1answer
25 views

Symbol to indicate normalized or standardized variables

Is there a symbol to indicate that variables have been standardized? For example, if I have 2 different scoring functions Score1 and Score2. Let's say I want to form a combo score and show that the ...
0
votes
0answers
20 views

How should I normalize a difference of features?

Say I have two Feature vectors $\phi_1$ and $\phi_2$. Theoretically which of the following normalization alternatives would give greater average performance for a binary classification problem that ...
1
vote
1answer
51 views

Data normalization in k-means and svm

Generally if I want to normalize my data in which direction I should normalize (subtracting mean and dividing by std)? Lets say I have a data matrix D (...
1
vote
1answer
45 views

How to decide how to normalize a given feature in a data set?

I have two features that differ in their orders of magnitude and also in the way they are distributed. I am aware of two ways of normalization: 1) $\frac{x - x_{min}}{x_{max} - x_{min}}$ 2) $\frac{x ...
0
votes
1answer
50 views

Why do we need undirected (Markov) graphical models?

I understand the modular nature of directed models, and that each node captures a conditional probability. But why do we need undirected models? As far as I can see they lack intuition in that the ...
0
votes
0answers
13 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?
4
votes
1answer
75 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?
0
votes
0answers
25 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 ...
1
vote
2answers
74 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, ...
0
votes
0answers
14 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 ...
2
votes
1answer
84 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 ...
0
votes
0answers
14 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 ...
0
votes
0answers
26 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 ...
1
vote
0answers
50 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 ...
0
votes
0answers
68 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 ...
0
votes
0answers
32 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 ...
1
vote
0answers
46 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 ...