Linked Questions

54 votes
2 answers
188k views

scale a number between a range [duplicate]

I have been trying to achieve a system which can scale a number down and in between two ranges. I have been stuck with the mathematical part of it. What im thinking is lets say number 200 to be ...
Saneesh B's user avatar
  • 643
4 votes
2 answers
14k views

What are the real benefits of normalization (scaling values between 0 and 1) in statistics? [duplicate]

I am working on student data set in which I want to normalize the range of percentage to 0,1. But I am not clear with the actual benefits of normalizing a range.
INDERJEET SINGH's user avatar
1 vote
1 answer
517 views

Data normalization choice [duplicate]

What are the main advantages and disadvantages of normalization between 0 and 1 or the other zero mean variance one algorithm? If we want to preprocess the data, how to select either of these two ...
MikiBelavista's user avatar
1 vote
0 answers
120 views

Which is better to normalize data? [duplicate]

I saw on Coursera machine learning classes that is possible to normalize data in two ways: data = (data - mean) / max(data) - min(data) or you can use an Octave ...
Pasdf's user avatar
  • 53
76 votes
4 answers
157k views

Is standardization needed before fitting logistic regression?

My question is do we need to standardize the data set to make sure all variables have the same scale, between [0,1], before fitting logistic regression. The formula is: $$\frac{x_i-\min(x_i)}{\max(...
user1946504's user avatar
  • 1,337
56 votes
4 answers
83k views

Normalization vs. scaling

What is the difference between data 'Normalization' and data 'Scaling'? Till now I thought both terms refers to same process but now I realize there is something more that I don't know/understand. ...
d.putto's user avatar
  • 921
25 votes
5 answers
37k views

Creating an index of quality from multiple variables to enable rank ordering

I have four numeric variables. All of them are measures of soil quality. Higher the variable, higher the quality. The range for all of them is different: Var1 from 1 to 10 Var2 from 1000 to 2000 ...
user333's user avatar
  • 7,221
8 votes
1 answer
3k views

Quality-price trade-off

Say there are 3 companies A, B and C. Each company has a quality rating from 0 to 100 and a price in USD. ...
melhosseiny's user avatar
9 votes
2 answers
6k views

Should I normalize featurewise or samplewise

It might be a beginner question, but I'm not sure how to normalize my data. Let's suppose I have a NxM matrix with N samples of M dimensions each. If I want to normalize my data I can do it in two ...
Elerium115's user avatar
5 votes
1 answer
7k views

Rescaling vs Standardization of features

Is there any general rule of thumb or any justified rule to choose whether to scale a dataset using Rescaling (for each feature, subtract the min value and divid by the max - min) or Standardization (...
eLearner's user avatar
  • 115
2 votes
1 answer
9k views

How to use the squared exponential kernel with multidimensional vector inputs?

I'm constructing an optimization (Bayesian optimization) algorithm using Java code. I have created the program, but the similarity values between inputted vectors in the kernel equation does not ...
Cooper Scher's user avatar
0 votes
1 answer
5k views

Data normalization in SPSS statistics

I am analyzing the responses of a survey using spss statistics. I understand that I will need to do a Cronbach alpha first. But here is my problem: The first part of my survey is "Awareness" and ...
user90940's user avatar
7 votes
1 answer
2k views

"Robust" normalization of features from multiple groups and unknown distributions prior to learning

I'm working on a machine learning project involving statistical analysis (and later discriminatory classification) of different proteins (samples) drawn from multiple, potentially overlapping classes /...
GrimSqueaker's user avatar
3 votes
1 answer
1k views

Is L2 normalization of rows followed by min/max scaling the same as mean-centering and unit variance?

I'm following this guide on detecting anomalies using autoencoders. The section titled "Normalising & Standardising" seems to be describing normalization in terms of scaling and shifting ...
bli00's user avatar
  • 143
2 votes
1 answer
1k views

Process for Standardising and Normalising data

This is a problem which I've previously solved very naively. I'm looking to apply more standard statistical theory to this problem in an attempt to get more accurate results. Any help with validating ...
kissmyface's user avatar

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