Linked Questions

1
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0answers
39 views

R daisy - Gower distance, different values with different number of observations [duplicate]

I have a mixed data set where I want to compute distances between observations with Gower in R (daisy function). When I compute distances between different number of observations, the distances seem ...
0
votes
0answers
18 views

Is it correct to use “Ward.D2” 's method of R's hclust function with a Gower distance matrix? [duplicate]

I have mixed type variables (3 quantitative and 3 qualitative) and I calculated Gower's dissimilarity distance between my objects. I wanted to do a hierarchical clustering with hclust, but I am not ...
65
votes
6answers
94k views

Why does k-means clustering algorithm use only Euclidean distance metric?

Is there a specific purpose in terms of efficiency or functionality why the k-means algorithm does not use for example cosine (dis)similarity as a distance metric, but can only use the Euclidean norm? ...
34
votes
2answers
49k views

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 ...
19
votes
8answers
46k views

Clustering of mixed type data with R

I wonder whether it is possible to perform within R a clustering of data having mixed data variables. In other words I have a data set containing both numerical and categorical variables within and I'...
30
votes
1answer
41k views

Doing principal component analysis or factor analysis on binary data

I have a dataset with a large number of Yes/No responses. Can I use principal components (PCA) or any other data reduction analyses (such as factor analysis) for this type of data? Please advise how I ...
30
votes
2answers
26k views

How to use both binary and continuous variables together in clustering?

I need to use binary variables (values 0 & 1) in k-means. But k-means only works with continuous variables. I know some people still use these binary variables in k-means ignoring the fact that k-...
11
votes
1answer
14k views

What is the optimal distance function for individuals when attributes are nominal?

I do not know which distance function between individuals to use in case of nominal (unordered categorical) attributes. I was reading some textbook and they suggest Simple Matching function but some ...
9
votes
2answers
30k views

Clustering with categorical and numeric data [duplicate]

I frequently come across data sets that have both categorical and numeric data. I think this is just a fact of life where the data is not all in one category. I'm basically trying to find some ...
12
votes
2answers
18k views

How does the Gower distance calculate the difference between binary variables'?

I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. ...
5
votes
2answers
7k views

Can binary data be ordinal?

Binary data is often mentioned as a nominal sub-category, especially in such examples as female/male, smoker/non-smoker, etc. However, binary data with such values as pass/fail, correct/incorrect, ...
5
votes
2answers
12k views

Gower's (dis)similarity index

I would like to ask a question about Gower similarity/dissimilarity index. Is it ok to use the Gower dissimilarity measure with Ward linkage clustering? I was reading that the Gower similarity index ...
12
votes
1answer
6k views

Robust cluster method for mixed data in R

I'm looking to cluster a small data set (64 observations of 4 interval variables and a single three-factor categorical variable). Now, I'm quite new to cluster analysis, but I am aware that there has ...
4
votes
2answers
4k views

Convert categorical data to numerical data to compute a distance then

I want to calculate euclidean distances for a dataset I have. However, there are two attributes which are not numbers. One attribute is country(10 different countries), the other one is race(3 races). ...
1
vote
3answers
5k views

Ask for suggestions on clustering methods on a large dataset with mixed types of variables

I need to build segmentation on a large customer dataset with more than 300K records and many variables, including continuous like income and age, ordinal like education level and membership level, ...
4
votes
1answer
2k views

Ecological mixed data cluster analysis: Transformations required? Use K-means or hierarchical methods?

I am trying to identify habitat types from 85 plots. I intend to do a cluster analysis to identify habitat types, and hope to fit additional plots into the identified clusters. (For context, I took ...
3
votes
2answers
3k views

How to derive a distance function based on multiple variables for cluster analysis?

I am not a statistician, so please excuse my lack of statistics knowledge/terminology. I have bunch of network nodes that I want to run cluster analysis on and identify clusters. So as far as I ...
3
votes
3answers
1k views

Clustering numeric, categorical, and multivalue categorical data

I have data that look like this: ...
1
vote
1answer
2k views

coding survey data for cosine similarity and euclidean distance?

I want to know how to code survey data such that a similarity function can be applied on it. Say I want to use cosine similarity. All the search results and QA I've found while in my search deal only ...
0
votes
0answers
2k views

Distance metric for categorical and numerical data

I have asked a related question in mathematics section, but I think here is a better place to ask. for both KNN algorithm (classification) and k-means algorithm (clustering), there is a need for a ...
1
vote
1answer
1k views

How Gower's dissimilarity handle missing values in numeric columns?

I would like to ask a question about Gower dissimilarity, I was wondering how Gower measure handle missing values in numeric columns, especially that Gower standardized each column based on the range ...
1
vote
0answers
751 views

Gower's (dis)similarity: How are numeric values scaled?

I am trying to understand the concept of Gower's (dis)similarity measure and I have problems to understand the scaling method for numeric variables. Are numeric values just scaled between 0 and 1 ...
0
votes
1answer
651 views

Clustering Data Using Gower and Kmeans

I am trying to do clustering on my data which consists of both categorical and continuous variables. I have some questions which I would like to ask: I am going to use the Gower Distance measure to ...
0
votes
1answer
450 views

How to compute the centroid of a cluster for Gower distances

I'd like to assess how scattered a cluster of binary vectors $X_j$ is, and as I understand the conventional way for doing this is: $$ S = \frac{1}{T} \sum_{j}^{T}\|X_j-A_j\|_p, $$ where $A_j$ is the ...
2
votes
1answer
531 views

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 ...
1
vote
0answers
392 views

Cluster analysis in SPSS

I started learning cluster analysis (using SPSS) and I need some help in a practical problem. Given the following variables: The respondents were asked to indicate the importance of the following ...
1
vote
0answers
274 views

Clustering on a data set with mixed variables [duplicate]

I have a data set consisting of $n$ elements with $d$ features for each element ($x_{i,f}$ means the value for the f-th feature of the i-th element). I would like to cluster this data set into $k$ ...
3
votes
1answer
119 views

Clustering patients according to biomarkers: an easy way out?

I've just started reading about clustering and classification. It's a djungle, a fascinating one. Currently, however I have a rather urgent task, i.e to perform a sort of cluster analysis in the sense ...
0
votes
1answer
182 views

Clustering with respect to multiple metrics

Hierarchal clustering methods as well as some others such as DBSCAN use a notion of (dis-)similarity between data points to cluster the data. Such dissimilarity can be formalized by the mathematical ...
0
votes
0answers
158 views

Non-parametric Clustering for mixed-type data

Currently I am studying Cluster Analysis where I am going through the TwoStep clustering method found in SPSS (it is a futher developed BIRCH method). Does anyone know what can be used as an ...
1
vote
1answer
101 views

FindSimilar items in a complex dataset

Im a MachineLearning newbie, but I want to learn more about this interesting topic using a practical example, on which I would appreciate any theoretical and practical help: I have a database of "...
2
votes
0answers
98 views

What is an appropriate way to re-scale ordinal features, for cluster analysis? AND any thoughts on euclidean-distance for ordinal data?

Background I have data from surveys (on political views from CSES) with answers from respondents in ranking-scales, either 0:10 (0, 1, 2, ..., 10) or 0:3 (0, 1, 2, 3). I want to analyze this data ...
0
votes
1answer
81 views

Hclust in R - Categorical data with multiple categories

I have a dataset with 266 observations with categorical variables of multiple categories. I am using the function hclust in R and the function ...