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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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133
votes
5answers
90k views

What's the difference between principal component 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?
18
votes
3answers
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? ...
2
votes
1answer
2k 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% ...
19
votes
5answers
6k views

Are there any versions of t-SNE for streaming data?

My understanding of t-SNE and the Barnes-Hut approximation is that all data points are required so that all force interactions can be calculated at the same time and each point can be adjusted in the ...
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
400 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 ...
21
votes
1answer
6k views

t-SNE versus MDS

Been reading some questions about t-SNE (t-Distributed Stochastic Neighbor Embedding) lately, and also visited some questions about MDS (Multidimensional Scaling). They are often used analogously, ...
12
votes
4answers
12k views

Performing PCA with only a distance matrix

I want to cluster a massive dataset for which I have only the pairwise distances. I implemented a k-medoids algorithm, but it's taking too long to run so I would like to start by reducing the ...
11
votes
2answers
4k 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 ...
6
votes
2answers
3k views

MDS on large dataset (R or Python)

I have a large 400000 $\times$ 400000 dataset (dissimilarity matrix) and I want to do multi-dimensional scaling on it. However, after looking at the generic cmdscale() function in R, it only takes ...
6
votes
3answers
5k views

Multiple regression - how to calculate the predicted value after feature normalization?

I'm currently doing the Andrew Ng machine learning course on coursera, and in Week2 he discusses feature scaling. I have seen the lecture and read many posts; I understand the reasoning behind ...
4
votes
2answers
551 views

How to reduce the dimensionality of a similarity matrix (of categorical co-occurence counts)?

Our example person Azra has assigned (open-ended categories of her own choosing) to a fixed set of 35 items, recorded as logical values (...
6
votes
1answer
5k 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 ...
3
votes
1answer
4k 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 ...
3
votes
2answers
1k 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 ...
1
vote
0answers
900 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 ...
4
votes
1answer
919 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 ...
2
votes
0answers
2k views

Gower distance and MDS: How to determine which variables count?

I have morphological data from two different determined groups (It and Nd), where the variables are heterogeneous (continuous, ...
2
votes
1answer
914 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
0answers
262 views

NMDS anomaly - data does not support point placement

My data: Tracking forest communities (via species abundances) in various forest plots across time. My approach: Non-metric Multidimensional Scaling ordination I performed NMDS (using ...
0
votes
0answers
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 ...