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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7 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 <...
3
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1answer
22 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 $e_i$ ...
2
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0answers
24 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, ...
4
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2answers
34 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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0answers
26 views

Analyse the data of two responses while having two different scales

I am working on data analysis these days and stuck on analysis when I have to compare and analyse two kinds of responses. Responses are of similar nature. First, I have gathered the data on the self ...
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0answers
48 views

What is the most effective way to get a baseline rating prediction from netflix rating data?

I am doing an assignment where I am working with some of the Netflix Challenge data. I have a database that maps movie ids to customer ratings of that movie and a database of customers mapped to ...
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0answers
33 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 ...
4
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1answer
100 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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0answers
10 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
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1answer
70 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 ...
0
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2answers
68 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: ...
5
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1answer
62 views

Finding optimal correspondences between objects given two square distance matrices

I would like to find the optimal correspondences between two systems of objects based on the distances between objects WITHIN the two systems. So, the input to the algorithm would be two square ...
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23 views

ordination of non gaussian data

I'm trying to ordinate a quite big dataset (44 variables with scaled values between 0 and 1, with 800 observations), with evident correlations between them (both spearman and pearson pairwise r ...
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1answer
33 views

Detect outliers in multi dimenstions

I tried to implement outlier detection for one dimension using inter quartile. for instance , a given variable cost or revenue or profit. but I'm missing outliers in other dimensions when running for ...
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0answers
29 views

How can I scale the $k$-th moment of a time series to a different time frequency?

I have a time series, let's say N daily log-returns. I want to study the moments (possibly the distribution) of the weekly returns. I have two ways: 1) Using the time-additivity property of ...
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0answers
28 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-...
0
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1answer
46 views

randomForest MDSplot help R

I am new to R and randomForests so bear with me. I am trying to visualise my randomForest a little better using the MDSplot() function in Random Forest. There are two things i would like to do, and i ...
0
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0answers
49 views

How could a hyperparameter grid search be visualised?

Consider a hyperparameter grid search that looks at the training and testing scores of an estimator with respect to multiple parameters like training epochs, number of nodes in layer 1, number of ...
3
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1answer
428 views

Input Normalisation for ReLU neurons

According to LeCun (1998) it is good practice to normalise all inputs so that they are centred around 0 and lie within the range of the maximum second derivative. So for example we would use [-0.5,0.5]...
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0answers
36 views

how to calculate the variance contribution of individual coordinates for multidimensional scaling analysis

I have searched the CrossValidated and stak Overflow and found the following related threads, Standard method for calculating contribution of individual variable to outcome Non-metric Stress in 3 ...
0
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1answer
43 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....
3
votes
1answer
41 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 ...
2
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0answers
29 views

How to determine the number of random initializations to use in non-metric multidimensional scaling?

I'm trying to determine how many random initializations (restarts) I should use when performing an nMDS ordination. I understand I want to choose the solution that minimizes the stress, but how many ...
3
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1answer
130 views

Does Dimensionality curse effect some models more than others?

The places I have been reading about dimensionality curse explain it in conjunction to kNN primarily, and linear models in general. I regularly see top rankers in Kaggle using thousands of features on ...
0
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0answers
45 views

scale and rescale the data predicted from neuralnetwork

i am trying to use neuralnet or mlp function on my data and then iuse to predict on my test data output [B], at the beginning i am using this code to rescale my data : maxs <- apply(data, 2, max) ...
3
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3answers
371 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 ...
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0answers
69 views

Proper way to do multivariate analysis of relative abundance data table

I have a data table, which is a result of running software MetaPhlAn. The values are relative abundances of each microbe taxon in samples. Samples are independent of each other. I want to know how ...
5
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1answer
147 views

In multidimensional scaling, how can one determine dimensionality of a solution given a stress value?

In multidimensional scaling, how can one determine dimensionality of a solution given a stress value? From what I understand, stress value is inversely related to the number of dimensions of a MDS ...
0
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0answers
15 views

Manual multidimensional scaling in R

Given a matrix A, I want to complete Multidimensional Scaling by hand, instead of using any given R functions. As such, I have calculated the centered matrix ...
2
votes
2answers
49 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 ...
3
votes
1answer
85 views

Interpret multidimensional scaling plot

I have data with 4 observations and 24 variables. To understand the underlying relationship I performed Multi-Dimensional Scaling (MDS), and got a plot like this: Now the issue is with the correct ...
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1answer
65 views

Unsupervised Learning on Multilevel/Multidimensional Data

I am working on a case-control study, where I for each individual have high dimensional data (like illustrated in the image). I would like to do both PCA analysis and Clustering on this data, but ...
0
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0answers
26 views

NMDS on data with different measure units

Is it correct to apply non-metric multidimensional scaling(NMDS) on data with different measure units and so, different ranges? Is there the possibility that the variable with higher values (due to ...
1
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0answers
30 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 ...
1
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1answer
261 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?
1
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0answers
292 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 ...
0
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0answers
182 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 (...
0
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0answers
308 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....
3
votes
1answer
90 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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0answers
37 views

Clustering before or after ordination

Can someone explain the implications of performing clustering either before or after performing NMDS? I have some ecological data and I am performing a clustering analysis to identify communities of ...
1
vote
1answer
70 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 ...
4
votes
1answer
195 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 ...
1
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1answer
1k views

interpreting NMDS ordinations that show both samples and species

I am using the vegan package in R to plot non-metric multidimensional scaling (NMDS) ordinations. I am using this package because of its compatibility with common ...
1
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0answers
118 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 ...
3
votes
0answers
697 views

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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0answers
186 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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vote
0answers
174 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 ...
2
votes
1answer
188 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 ...
0
votes
1answer
20 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 ...
2
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0answers
185 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 ...