Technique that renders observed or computed (dis)similarities among objects into distances in a low-dimensional space (usually Euclidean). It thus constructs dimensions for the data; the objects can be plotted and conceptualized in those dimensions

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18 views

Is it correct to combine PCA and NMDS axes in a multiple regression?

I am considering to do a multiple regression in which some of the predictive variables are PCA (principal components) axes whereas others are NMDS (nonmetric muliple dimension scaling) axes. I would ...
2
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1answer
54 views

Multidimensional Scaling “eurodist”

I have a question regarding Multidimensional Scaling. I used the dataset eurodist from the package datasets to generate a 2 ...
0
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1answer
115 views

Multidimensional scaling using Python

I have 6,000 points for which I have all pairwise distances in a distance matrix. I want to get an idea whether these data were generated by a mixture of Gaussian distributions so I'm trying to get a ...
1
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0answers
23 views

Multidimensional scaling of variables with multiple sub-features?

Let's say I have a year's worth of magazine issues (January, February, March, etc), and I want to visualize the differences among them. The classic example of multidimensional scaling (MDS) would have ...
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0answers
39 views

Scaling data in machine learning algorithm

I am currently working on a linear classifier, which uses the statistical learning paradigm; that is, no knowledge about the distribution from which that training data are drawn from is available. ...
1
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0answers
32 views

Steps to follow for correspondence analysis when each brand is not shown to every respondent

I want to understand the steps followed for correspondence analysis when each brand is not shown to every respondent. Till now I used to assign a number (proportion) to each brand for each attribute ...
1
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1answer
123 views

Guttman's smallest space analysis

I am trying to replicate an analysis as conducted by Raven, et al. (1998). A scale is analyzed with Guttman's smallest space analysis. First of all I wasn't able to find a suitable procedure in R and ...
1
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1answer
70 views

Kernel PCA with an SVD algo

Suppose that I have a great algo for calculating the SVD and I want to do Kernel PCA. It is possible to first apply the Kernel function to my data and then run the SVD algo on the transformed data?
1
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1answer
57 views

Multidimensional quantiles

I have 1000 observations with 2 continuous variables : Observation ID | X | Y
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0answers
165 views

Multidimensional Scaling in R with Spearman's Rank Correlation

I'm new to MDS, but I found some good starter code here (http://mhermans.net/static/postdata/r-examples/neighbours-mds/neighbours-mds-example.html) and which I borrowed for below. The code works fine, ...
2
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2answers
181 views

Perform feature normalization before or within model validation?

A common good practice in Machine Learning is to do feature normalization or data standardization of the predictor variables, that's it, center the data substracting the mean and normalize it dividing ...
1
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1answer
50 views

Which values to use for scaling out of sample PCA data

I have centered and scaled inputs via prcomp (): prOut<-prcomp(trainSet[,2:4],scale = TRUE,scores=TRUE) I now want to use ...
0
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0answers
45 views

Transforming distance matrix to univariate data

Is there a valid mathematical or statistical approach to converting site by site distance objects/matrices to a univariate site vector or column in a dataframe? I have a Euclidean distance matrix for ...
2
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0answers
71 views

Why does some model-based clustering fail to fit with a large number of dimensions?

I am attempting to cluster data using Mclust. The data is originally from a dissimilarity matrix, transformed via multidimensional scaling in R (MASS::isoMDS). As I ...
2
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0answers
110 views

whether to rescale indicator / binary / dummy predictors for LASSO

For the LASSO (and other model selecting procedures) it is crucial to rescale the predictors. The general recommendation I follow is simply to use a 0 mean, 1 standard deviation normalization for ...
0
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1answer
108 views

Analysing data measured as proportional composition

I have a data set on the proportional composition of marine substrate for different locations which I would like to compare. For example, one replicate transect within a location may be 50% sand, 25% ...
1
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0answers
22 views

Issue of multiple scaling method

I plan to use multiple scaling in R and start with a toy example. There are two matrices. The first contains 10 observations and the second one contains two replicated rows. It appears that the ...
2
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0answers
24 views

How to enhance the performance of naive CMDS?

I'm performing Classical MDS on the distance over columns of binary matrix. The result is like this: The points lies on two lines vertical to each other. I don't think useful information is shown ...
8
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3answers
226 views

How to project high dimensional space into a two-dimensional plane?

I have a set of data points in a N-dimensional space. In addition, I also have a centroid in this same N-dimensional space. Are there any approaches that can allow me to project these data points into ...
3
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1answer
210 views

MDS and PCA eigenvalues and eigenvectors

I understand that Multidimensional scaling (MDS) is same as doing Principal Components analysis (PCA) if Euclidean distance is used, this is known as Metric MDS. But I came across this in a book that ...
0
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0answers
55 views

Multidimensional scaling

I am running into some problems performing a multidimensional scaling image. First of my dataset is quite large (330.000 fields: 33000 rows, 10 columns). The output image needs to contain 10 dots, 1 ...
0
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1answer
85 views

NMDS: why is the r-squared for a factor variable so low

I am doing an NMDS ordination. The data come from a number of sites scattered around two lakes. In the plots, I coloured the samples from the two lakes blue and green. There seems to be some pretty ...
2
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1answer
239 views

NMDS and variance explained by vector fitting

I just ran a non metric multidimensional scaling model (nmds) which compared multiple locations based on benthic invertebrate species composition. After running the analysis, I used the vector fitting ...
-1
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1answer
67 views

NMDS for biomass

I would like to make a NMDS with biomass of different prey groups in stomach content of fish. I have already made one where the data matrix consists of 0 and 1, and this one went fine but are not ...
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0answers
119 views

R - Multidimensional Scaling and Missing Values

I include MDS analysis in a customer survey and have about 10 brands I want to include in the perceptual map at the end. Meaning the customers would have to rate 45 comparisons and give a similarity ...
4
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2answers
446 views

How to best display crosstab data?

I have a 10x10 matrix composed of two variables with 10 brands each. One variable is the brand purchased, the other is the brand considered. My matrix shows a crosstabulation between the two. I need ...
1
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0answers
52 views

The proper scaling for generating uniformly distributed points in the n-d ball of *non-unit* radius?

The question of generating uniformly distributed points on the surface of n-dimensional unit ball has been already posted here a dozen of times. What I'm interested in is the proper scaling when we ...
0
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1answer
138 views

How to scale new datas when a training set already exists

Here is what I have : A scaled training set, with labels. Segmented images, from which I extract new vectors to classify. My classifier is a KNN which would have obviously been trained using my ...
0
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0answers
115 views

Finding the projection used in multidimensional scaling

Background I have a set of data points in high-dimensional (512D) space that I wish to map to 2D for visualisation. I am interested in observing in 2D the (approximate) relative distances between the ...
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0answers
298 views

Multidimensional scaling on distance or similarity matrix

Why doesn't the scatter plot change when I perform multidimensional scaling on distance or similarity matrix? This figure uses similarity matrix And this figure use distance matrix ...
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0answers
31 views

Separate points in 3 or more dimentions into 2 groups with labels A and B

How can you separate a group of points in 3 dimensions into two groups with labels A and B? My approach: If we draw a plane through the cloud of points, the group A can be the points above the plane, ...
3
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0answers
36 views

Multidimensional scaling of random matrix

Suppose I have a random symmetric matrix W of size $n\times n$, with i.i.d. coefficients uniformly distributed in [0,1], and I set $W_{ii} = 0$. Then I apply a Multidimensional Scaling of dimension ...
2
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1answer
121 views

Individual differences scaling, additional investigations

I am learning individual differences scaling (AKA three-way multidimensional scaling) and I want to know what different ways there are to state that my results are reliable. I had to perform ...
1
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0answers
61 views

Sequential or dynamic multidimensional scaling

I am looking for a way to conduct sequential (dynamic) MDS based on several variables coded for a sequence of stimuli. Could anyone direct me to software for this purpose (especially R packages / ...
2
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0answers
301 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) ...
1
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1answer
100 views

Is first dimension more informative in multidimensional scaling?

A property of Principal Components Analysis (PCA) is that the first dimension is the most informative, next the second and so on. Is this property true also for multidimensional scaling (MDS)?
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0answers
148 views

Non-metric multidimensional scaling with dichotomous independent variables?

I have a set of t-rflp fragment-length profiles from an investigation into microbial degradation of hydrocarbons as part of my undergrad dissertation. I want to study the effect of various variables ...
9
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1answer
3k views

RandomForest - MDS plot interpretation

I used randomForest to classify 6 animal behaviours (eg. Standing, Walking, Swimming etc.) based on 8 variables (different body postures and movement). The MDSplot in the randomForest package gives ...
1
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0answers
44 views

Computing and comparing semantic networks generated by grouped individuals

I have 2 groups, each containing 20 individuals. For each individual I have a dissimilarity matrix of a number of judged items. I'd like to evaluate whether there is an overall difference between the ...
1
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3answers
268 views

Metric and Clustering Method

I need some suggestions regarding what kind of metric and clustering analysis I should use. I read a lot of posts but didn't get any hints about this type of data. I have a 3000*5000 matrix, where ...
0
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1answer
90 views

Is a Biplot suitable ? Domestic Violence VS Non-Violence data

I have a small data set that consists solely of counts. I have several variables. For example State, for each state (Mexican States), for example, Tamauplipas I have the counts of domestic violence ...
0
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1answer
120 views

Methods of “Two-Way” Multidimensional Scaling (MDS)?

I just want to ask about the MDS. Below is the subcategory of the Multidimensional Scaling topic. Multidimensional Scaling Metric and Non-Metric Models Methods of "Two-Way" Multidimensional Scaling ...
11
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2answers
667 views

What is the role of MDS in modern statistics?

I recently came across multidimensional scaling. I am trying to understand this tool better and its role in modern statistics. So here are a few guiding questions: Which questions does it answer? ...
3
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0answers
202 views

Quantifying differences in a discrete distribution across several populations

Suppose you have a discrete random variable, $Y$, with a large number (say, $300$) of discrete (which happen to be nominal) possible outcomes. The mass function, $p(y)=P(Y=y)$, is unknown but a sample ...
0
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1answer
2k views

How can I calculate the R-square value of an MDS to assess the fit of the model to the data in R?

I would like to do Multidimensional Scaling (MDS) using cmdscale() in R. I have read that it is useful to try out how many dimensions are suitable for the data by ...
41
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4answers
12k views

What's the difference between principal components analysis and multidimensional scaling?

How are PCA and classical MDS different? How about MDS versus nonmetric-MDS? Is there a time when you would prefer one over the other? How do the interpretations differ?
4
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1answer
1k views

Interpretation of MDS factor plot

Suppose I run Multidimensional Scaling and I got the resulting plot. Can anybody suggest me how to interpret the plot. Please find one of my result below. Here I've 5 concepts which I run the MDS ...
7
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2answers
947 views

Visualizing multi-dimensional data (LSI) in 2D

I'm using latent semantic indexing to find similarities between documents (thanks, JMS!) After dimension reduction, I've tried k-means clustering to group the documents into clusters, which works ...
5
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2answers
347 views

Big-O Scaling of R's cmdscale()

I'm trying to run R's multidimensional scaling algorithm, cmdscale, on roughly 2,200 variables, i.e. a 2,200x2,200 distance matrix. It's taking forever (about a ...
5
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2answers
2k views

Multidimensional scaling pseudo-code

I am planning to write a program that performs MDS. Any pointers to where I can access the pseudo-code for MDS? Thanks!