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4
votes
1answer
929 views

Normalizing data before applying MDS with strain criterion

The features of my dataset are like below: • BI-RADS assessment: 1 to 5 (ordinal) • Age: patient's age in years (integer) ...
3
votes
1answer
748 views

Feature scaling/normalization and prediction

I have a dataset which I have split into a training and a test set. I have thereafter applied normalization on the training set and saved the mean (U) and standard deviation (SD) estimated based on ...
3
votes
1answer
3k views

Scaling/Normalization not need for tree based models

I could not find a good answer/reference that can explain why rf/decision trees/gbm are not susceptible to the scale of values of numerical variables. My sense is that since boosting methods ...
3
votes
1answer
304 views

Is normalization required in Sammon mapping

I have a data set of 480 samples with 7-dimensions and I want to implement a Sammon mapping into 3-dimensions. In Principal Component Analysis to my understanding we need to normalize the data in ...
3
votes
1answer
333 views

Why normalize data after doing Multidimensional scaling?

I am running simulations from a paper on graphical clustering based on latent positions. Essentially, the first step is to do Multidimensional Scaling on the Adjacency matrix, after which the authors ...
2
votes
2answers
237 views

Support Vector Regression and Data Rescaling

I am currently working on Support Vector Regression and I've read that it is recommended to implement data rescaling, e.g. to interval $[-1;1]$, to obtain better results. My first question is: should ...
2
votes
1answer
919 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 ...
1
vote
1answer
114 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 ...
1
vote
0answers
809 views

Pros and Cons of MinMax Normalization vs. Standardization

I have a large dataset with 800 columns and 6,000,000 rows with many dummy variables (70%+). I want to Normalize it. Given that so many variables are binary, taking values 0 or 1, I am tending ...
0
votes
1answer
310 views

Is it necessary to deal with the outliers if we perform Normalisation on the data?

I am wondering, if it is necessary to remove outliers from the dataset if we perform Normalisation on the data as after Normalisation, all the values will shrink to value between 0 and 1. So, is it ...
0
votes
1answer
701 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 ...
0
votes
0answers
57 views

Feature scaling and when to use which

I am looking into running regression on a multivariate data set. I am looking into different ways to scale my data: standardization, L2 and L1 normalizations. In what case would you use which method? ...
0
votes
0answers
137 views

How to normalize three variables into one ordinal scale?

I have three same scaled variables (Strategy 1: Stay, Strategy 2: Move, Strategy 3: Move far) which I want to compare in a heatmap for different locations. For each strategy an operator earns a ...