Questions tagged [multidimensional-scaling]

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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143 views

How to perform multidimensional scaling where a subset of points are already fixed?

I have two sets of psychological variables. For simplicity, there is set A (10 variables) and Set B (10 variables). When you map Set A using two-dimensional multidimensional scaling (e.g., using <...
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1answer
943 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) ...
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1answer
535 views

Learning vector embeddings from distances

So... I have a set of entities $\mathcal{E} = \{e_i \mid i \in [1,n]\}$, and I have a proper distance metric defined over $\mathcal{E}\times\mathcal{E}$, call it $d$, so the distance between $e_i$ ...
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747 views

Is it legit to run clustering on MDS result of a distance matrix?

I am new to the topic of clustering and face the following problem: I have multiple binary datasets with 10k to 40k entries and 135 features each: $$ \begin{matrix} \newcommand{\feat}{\text{feat}} \...
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1answer
941 views

MDS: Is Kruskal's Stress-1 affected by scale of the data, or the number of points?

In Multidimensional Scaling, Kruskal's Stress-1 is a commonly used measure of fit. It is defined as: $\sqrt{\frac{\sum (d_{ij}-\delta_{ij})^{2}}{\sum d_{ij}^{2}}}$ where $d_{ij}$ represents the ...
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58 views

MDS: Are there measures of stress that are not affected by the number of objects?

This question flows naturally out of a previous question, in which it was explained that Stress-1 is somewhat impacted by the number of objects. You can assume that the number of objects in the ...
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2answers
177 views

How do I apply MDS analysis on my data set?

Consider the following dataset (it is the emission probability matrix of a Hidden Markov Model): ...
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2answers
2k views

Do we have to scale new unseen feature data for prediction

In machine learning most algorithms require some kind of scaling to decrease error. This is my code: ...
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1answer
425 views

Using metric MDS with non-metric distances and assessing the fit quality

I'm going to perform MDS by means of cmdscale function of standard R library. I spent several hours googling it and finally have ...
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46 views

Does it makes sense to perform MDS when $n<p$?

According to the reference quoted below, when performing a classical MDS on a dataset, I have to compute a centered matrix $B$ based on the dissimilarity matrix and then to compute the eigen-...
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1answer
848 views

Multidimensional Scaling “eurodist”

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

How to recursively normalize my histogram count

I need to scale my histogram as I cannot store them with large numbers. Hence, I need to normalize it. I have taken normalization factor as sum of total population. But this need to happen recursively....
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1answer
170 views

Multidimensional Unfolding permutation test with smacof package - What does p.value mean here?

I have a dissimilarity data matrix with 7 rows and 7 columns (two ways). Having done unfolding on it, I wanted to evaluate the observed stress value. Using permutation test with 1000 replication, the ...
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1answer
340 views

What does “ideal points” mean in multidimensional unfolding?

I am reading some materials about multidimensional unfolding and this concept "ideal points" are mentioned several times. I check these readings several times and could not find definition of this ...
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1answer
172 views

Multidimensional scaling [closed]

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 ...
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2answers
261 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 ...
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1answer
13k 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 ...
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4k 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 ...
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52 views

What's right/wrong with using multi-dimensional scaling to analyze voting patterns of for members of an 11-member city council?

I'm trying to analyze voting patterns of an 11-member city council over a period of five years. Description of data file: each row (vector) is labeled as a councilmember; each column records ...
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1answer
2k views

The `Shepard` function in R package `MASS`

The function Shepard is listed in the help file for MASS::isoMDS, but nothing is said about it. What does this function do?
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882 views

Using similarity measures as distances

I have a matrix where each row corresponds to an observation with binary attributes, and I am interested in performing multidimensional scaling using cmdscale on ...
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460 views

Representing experimental data by unconstrained ordination: PCA, PCoA, or NMDS?

I have a dataset composed by presence of different bacterial families in function at different pesticide treatment. I need to find a good representation of my data but I don't know which method (...
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2k views

Fitting various environmental variables to an NMDS

I have two sets of environmental variables (e.g. river flow and river temperature statistics). I would like to assess which of these explains the highest amount of variance of a community community (e....
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1answer
260 views

Using a distance matrix *with errors* to find the coordinates of points

(I asked this same question in stackoverflow, without getting any answer, but maybe this is a more appropriate forum.) I would like to find the coordinates of a set of points in 3D from a distance ...
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2answers
7k views

How to calculate the R-squared value and assess the model fit in multidimensional scaling?

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 ...
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1answer
506 views

Similarities and dissimilarities in classical multidimensional scaling

I am having trouble reconciling between several terms in MDS. According to [1], Section 14.8, Classical MDS takes similarities as inputs. In [2], also cited in Wikipedia, Classical MDS takes ...
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392 views

Apply trained MDS model to new data

I have both a distance matrix and the original vectors, and am using MDS (Multidimensional Scaling) with R to generate vectors in more dimensions for the data. With dimensionality reduction (for ...
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non-metric multi-dimensional scaling in R: help with plotting and understanding Stress for isoMDS vs. metaMDS

I have a dataframe with 900 observations. There are 11 columns: 9 measured variables and 1 representing region. ...
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1answer
7k views

How to interpret variation explained by principal coordinates?

I have recently seen a couple of Principal Coordinates Analysis (PCoA) projection plots which show "percentage variation explained" by the respective principal coordinates. Given that the analysis is ...
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714 views

Using Non-Euclidean Distance Matrix in Multi-Dimensional Scaling

I'm trying to use a non-euclidean distance matrix in MDS. Specifically, I'm using cmdscale in R. The resulting eigen vector appears to have huge negative values. From what I've read it appears that ...
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792 views

Goodness of fit for multi dimensional scaling

What is considered to be an acceptable value for goodness-of-fit in multi-dimensional scaling (MDS). I tried to run an MDS analysis on my data with four dimensions in R. The goodness of fit comes ...
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1answer
30 views

Analysis of microbial community data collected from iPad swabs

We have taken a number of swabs (~200) from iPads used in our clinic, and after the first half we've introduced an intervention to disinfect all iPads after every use (in addition to the standard ...
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1answer
1k 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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579 views

Non-metric Stress in 3 way Multidimensional Scaling (INDSCAL): individuals vs. group

My data consists of 19 participants giving dissimilarity ratings for every possible pairwise comparisons of a set of 12 epistemic adverbs (so each participant gives 66 ratings). The goal is to ...
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736 views

Understanding differences between large and small dimensional data when implementing algorithms

I'm working on a local outlier factor implementation based on the wikipedia entry : http://en.wikipedia.org/wiki/Local_outlier_factor This article seems to explain it in just two dimensional data. ...
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281 views

Reference for dimension reduction techniques

This is a follow-up question to Is PCA appropriate for comparing subsets of panel data?. It turns out that, yes, PCA is appropriate. But there are also many other ways to reduce n-dimensional data to ...
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935 views

nMDS in vegan for soil data

I am working with abiotic soil data such as bulk density, moisture levels and soil chemistry as response data (some quantitative some as percentages) and a mix of abiotic and biotic data as ...
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1answer
34 views

should weights be scaled too?

I am using supervised learning algorithms (specificly SVM) on my data. I know that scaling was needed for my input data. however as I am also adding weights (using pairwise comparison), I am not sure ...
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55 views

Using the results of a non-metric multidimensional scaling to derive a measure of deviance

I'm working with a dataset containing the taxonomic compositions of floras all over the world and performed a non-metric multidimensional scaling (NMDS) based on the relative proportions of plant ...
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1answer
928 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
702 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
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 ...
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1k views

How to distance and to MDS-plot objects according their complex shape

Suppose I have four basal forms of signal (blue, purple, red, green). I also have created transition forms between each other. If you carefully look on the picture below, you can see that for example ...
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1answer
309 views

Is it posible to perform the inverse of multidimensional scaling analysis

We have lot of 3D data and we reduced it to 2D for performing fuzzy clustering and obtaining prototypes. We used some matlab functions that were very well documented. Now we would like to see to which ...
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120 views

Suitable plot for 5 dimensional feature vectors?

I have a list of personality scores obtained from 100 people, based on the Big-Five personality test. Each person has one score for each of the five assessed traits. I put these scores into a 5 ...
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3k 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? ...
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265 views

When using Nonmetric Multidimensional Scaling, is there an explanatory metric similar to loadings in PCA?

As a beginner to MDS, here is my thought process: Given a data set of environmental factors that may effect a certain sites, when I run a PCA on each site I get a list of principal components. If I ...
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1answer
490 views

Multidimensional scaling for big dissimilarity matrix

I have a large symmetrical dissimilarity matrix of dimension 300 000. Can you please suggest the multidimensional scaling algorithms that can work with such large data? Input of course can be the ...
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372 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 ...
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1answer
717 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 ...