Linked Questions
24 questions linked to/from What is the optimal distance function for individuals when attributes are nominal?
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Hierarchical clustering with categorical variables - what distance/similarity to use in R? [duplicate]
I have only categorical variables in my database.
What distance/similarity to use?
I´m using the function simil() (library(proxy) in R.
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4
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F1/Dice-Score vs IoU
I was confused about the differences between the F1 score, Dice score and IoU (intersection over union). By now I found out that F1 and Dice mean the same thing (right?) and IoU has a very similar ...
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Choosing the right linkage method for hierarchical clustering
I am performing hierarchical clustering on data I've gathered and processed from the reddit data dump on Google BigQuery.
My process is the following:
Get the latest 1000 posts in /r/politics
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Hierarchical clustering with mixed type data - what distance/similarity to use?
In my dataset we have both continuous and naturally discrete variables. I want to know whether we can do hierarchical clustering using both type of variables. And if yes, what distance measure is ...
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With categorical data, can there be clusters without the variables being related?
When trying to explain cluster analyses, it is common for people to misunderstand the process as being related to whether the variables are correlated. One way to get people past that confusion is a ...
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Similarity Coefficients for binary data: Why choose Jaccard over Russell and Rao?
From Encyclopedia of Statistical Sciences I understand that given $p$ dichotomous (binary: 1=present; 0=absent) attributes (variables), we can form a contingency table for any two objects i and j of a ...
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3
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Understanding $\chi^{2}$ and Cramér's $V$ results
I have two groups of buyers, A and B, and I want to test whether the difference between the percentage of them who would buy a ...
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Hierarchical or TwoStep cluster analysis for binary data?
(This question is an edited version of a question I previously posted which one user recommended would benefit from more focus).
I have 2000 questionnaires from respondents which ask 33 different ...
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Accuracy vs Jaccard for multiclass problem
TL;DR For a multiclass problem, is Jaccard score the same as accuracy?
Update March 29, 2019
The wrong implementation in scikit-learn is now fixed with pull request #13151. Hooray!
P.S. The lesson ...
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Was it as valid to perform k-means on a distance matrix as on data matrix (text mining data)?
(This post is a repost of a question I posted yesterday (now deleted), but I've tried to scale back volume of words and simplify what I'm asking)
I'm hoping to get some help interpreting a kmeans ...
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Distance metric for all categorical data
I have categorical data in the form of Y/N of 23 attributes and containing 200+ records. I need to compute the distance between the attributes with their class label. Which metric can be used?
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Properties of Levenshtein, N-Gram, cosine and Jaccard distance coefficients - in sentence matching
Let's say I have two strings:
string A: 'I went to the cafeteria and bought a sandwich.'
string B: 'I heard the cafeteria is serving roast-beef sandwiches today'.
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4
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K-Means Clustering with Dummy Variables
I want to use k-means to cluster my data. I have broken one column into 4 dummy variables and I have normalized all of the data to mean=0 and sd=1. Will k-means work with these dummy variables?
I ...
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1
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NMDS from Jaccard and Bray-Curtis identical. Is that a bad thing?
The dataset is ecological (species abundance), where I am calculating distances between 51 sampling sites, based on abundances of 3200 species. The species abundance values go up to 2700, and the rest ...
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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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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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Dice coefficient: what is the effect of a smoothing factor?
I've come across code to calculate a Dice coefficient in imaging segmentation, in which a "smoothing factor" was added to the formula, as below (pseudo-code):
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Transform categorical variables for cluster analysis in R (mlr)?
Most clustering functions can't handle categorical variables. One way to deal with this is to transform them to binary integer variables (i.e. x in {0, 1}). This is straight forward for categorical ...
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1
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Measures of association between nominal variables with the same categories (paired nominal data)
Scenario: I am conducting a study in which I am comparing a ‘gold standard’ assessment protocol with an experimental assessment protocol for a health variable of interest, over a common set of study ...
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Distance calculation on variables that cannot be represented in the Euclidean space
Given a variable such as number of events attended together, which is more of a multi-dimensional data how can you calculate a sort of distance between people (i.e. ...
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Dummy data clustering: OK to apply Euclidian distance hierarchical clustering on Jaccard similarity matrix?
I created dummy variables (binary data) from categorical variables where I want to partition N subjects into multiple classes by some clustering method. I created a Jaccard similarity index matrix for ...
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Cluster analysis of large, multiple answer dataset
I have to analyse data from a marketing study. I will use SPSS. The questionnaire will look like this:
Q: Imagine Situation X. Select 1-3 Criteria from the list that best describe your feeling.
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Clustering variables of mixed types in R [duplicate]
I need to analyse questionnaire survey data with mixed data types (nominal, ordinal, continuous). I want to cluster the variables. So far I only have dead ends.
I know I can use daisy in the cluster ...
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Distance between nominal vectors: a review
I have a seemingly easy question which however is troubling me a bit.
I have couples of vectors made up of nominal attributes. They can be of different length and sometimes some of the attributes in ...
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