Questions tagged [clustering]

Cluster analysis is the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors and/or cluster-samples should be tagged as such; do NOT use the "clustering" tag for them.]

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Cluster Analysis via PCA (with mixed variables)

I have a fairly large dataset of 171 mixed variables (104 dichotomous/qualitative, and 67 continuous). My goal is to build a typology of agricultural systems. I originally used a PCA to reduce the ...
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What is the most appropriate way to cluster respondents based on their rankings of some items?

I have ~30 observations of individuals ranking 20 different products from top to bottom (1-20). I would like to have a way to "cluster" these individuals based on their rankings of the different ...
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35 views

Similarity measure/metric for long time series

I'm looking for a similarity measure/metric to cluster long time-series datasets. I feel that Euclidean distance won't do any good for my application, for it is not robust enough to detect patterns ...
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26 views

Classifying data, and then performing linear regression on the classes

Is it valid to perform a classification on a data set, separate the data by class, and then perform a regression on each of the groups? The reason why I ask is that the histogram for my data looks ...
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Using k-means clustering to train radial basis neural network for highly imbalanced dataset

I am trying to find prototype neurons for my radial basis neural network. My dataset has 30 attributes (of which 28 of them are the result of a single PCA) and 300.000 observations. It is a binary ...
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15 views

a proper way of clustering 3D vectors(XYZ) [on hold]

I am new to clustering and I need to cluster a set of vectors in cartesian space (3d vectors - XYZ in space). It means that I have three points in space with a force vector on each of them. I wanna ...
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9 views

n for Hopkins statistics using get_clust_tendency

I started to use the Hopkins statistics to establish, if a dataset is 'clusterable'. I am using the following code - taken from here: ...
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32 views

Running k-means clustering with k = 2 recursively on clusters greater than a certain size

Does it make sense to run k-means with k (number of clusters) of 2, and then for every cluster bigger than N, run k-means again with k = 2? We can then keep doing it until we have all clusters of size ...
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12 views

Interpretation of clustering on similarity matrix

Many papers suggest doing clustering not on the (n x p)raw data but on the n x n or p x p matrices computed according to determined similarity measures (eg, correlation, cosine, point mutual ...
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32 views

Hierarchical Clustering, Why Always Agglomerative?

I'm working on clustering for 6 month right now and there is question that bothers me lately, and that is why in every single resource about hierarchical clustering someone introduced two types of it (...
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37 views

Data standardization vs. normalization for clustering analysis

I'm performing clustering analysis and visualization (hierarchal, PCA, T-SNE etc.) on a dataset, and a bit confused about the method for data preparation. I understand that the typical options are to ...
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Can I use KernelPCA after using TruncatedSVD before clustering?

I am working on a project at a company where I have to make clustering/unsupervised model. The data I am working on is very sparse with high dimensions and after some research, I found out ...
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Analysing surprising clustering results in spectral clustering

I have two-dimensional data that I am trying to cluster. The data looks like this: I have been trying to cluster this using spectral clustering, as in ...
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Is it possible to label points as images [closed]

If I was researching brand logos could I plot so that instead of getting "Logo 1", "Logo 2" or "Adidas", "Mercedes", to get a image as their data point? It seems to me that it should be possible (in ...
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What neural network architecture can I use to take advantage of clusters in the data?

What neural network architectures can I use to take advantage of clusters in the data? In particular, I'm interested in doing a classification problem in which I believe that each cluster behaves ...
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46 views

Clustering - Use ARI to compare different clustering

I have a data set of 54000 genes and I used different methods for clustering such as HAC, K-means, model based clustering and CLARA. The objective is to compare these methods. I used the Adjusted Rand ...
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Anomaly Detection Without a Baseline

I am attempting to find anomalies in accounting data (similar to this study: https://arxiv.org/pdf/1709.05254.pdf). I don't have any labeled data, so this attempt needs to be unsupervised. I am having ...
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29 views

Train predictive model with predictive variable not present in production

Assume we are receiving a continuous time-series: $$X_1 = \{x_{1,1},\ldots,x_{1,n}\} \in \mathbb{R}^n$$ $$\vdots$$ $$X_i = \{x_{i,1},\ldots,x_{i,n}\} \in \mathbb{R}^n$$ At each step $i$ (knowing all ...
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similarities between objects [on hold]

I have a set of products which is produced according to a plan. All products will have a certain amount of attributes on how the products should be produced with a target value and some tolerance ...
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19 views

Creating the input for mcl algorithm

I would like to implement mcl (Markov clustering algorithm) in a dataset like this one: ...
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18 views

Finding the bottleneck in a set of trajectories

I have some 2D data which looks like the following: This can be seen as a plot of trajectories in 2D space, where the trajectories all pass through a point called the "bottleneck". What I want to do,...
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28 views

Is Hierarchical clustering a special case of knn(specific n=1)?

I'am working on time series in the scope of similarity detection at the moment. What seems to be a well researched approach is dynamic time warping in combination with k-1NN as classification ...
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20 views

Does PCA preserve convexity of a space?

I have a cluster $C$ of points in a high dimensional space $\mathbb R^n$. I want to know whether this cluster is convex or not. How can i study this? I thought of projecting $C$ on $\mathbb R^2$ to ...
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Why does the average linkage method put more emphasis on greater homogeneity then the Centroid Method?

at first i have to admit that i'am not an native english speaker. I hope i can articulate myself clearly. I read that the average linkage methode put more emphasis on greater homogeneity then the ...
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Adding Bootstrapped Parameters for Mclust Model-based Clustering

I have a data set that I have been working to cluster using model-based clustering with the package mclust. The clustering is one-dimensional (based on only one value per point), but each data point ...
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28 views

Can I use clustering as a filter of data?

I want to filter a dataset depending on the patterns of data. I think about clustering to do it. In the image of the middle there are some data points I want to filter(because they have a horizontal ...
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35 views

K-medoids algorithm for time series with varying lengths

Can time series having multiple lengths be clustered using the k-medoids algorithm. I am essentially looking for a way to find a representative pattern from a set of time series using the k-medoids ...
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In k-means clustering, is it convenient to include additional samples to the ones you are interested in?

I have a collection of numeric quantitative variables from a series of samples; let’s say, for example, countries from the whole world. My goal is to discern how countries can be distributed, ...
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59 views

Multiple tests with effects all in same direction but only few significant

I have tests done looking at the brain activity in 12 different regions of the brain. It is a between subject design where there is a treatment group (N = 8) and control group (N = 14). Each ...
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59 views

Unsupervised anomaly and outlier detection of database queries

I'm monitoring database queries coming from multiple different applications spread across numerous systems and I'd like to find both anomalous queries as well as outliers in a completely unsupervised ...
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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 ...
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24 views

Clustering Binary and Continuous Features

If you need to cluster a dataset with the following characteristics: It has a mix of binary and continuous features. It is very sparse. For most features, you only have values for 15% of the ...
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Panel data Clustering

I have panel data of variable X consisting of 15 yrs-time points and 103 countries. I want to cluster countries in four group. Please suggest appropriate method and software to run panel data ...
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Which distance metric to use to cluster categorical sequences (clickstreams or clickpaths)?

For my research, I want to cluster website visitors based on their clickstreams to understand different information behavior patterns (i.e., customer/visitor journeys). The data can be characterized ...
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What statistics can I use to describe the shape of a time series?

I want to apply a clustering algorithm to some time series datasets. I've tried DTW, but it hasn't quite achieved what I want (which is to cluster similarly behaving series such that I can tune ...
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Why does kmeans after SVD result in ideal clusters

I am clustering tweets which are related to eye fashion and they are extracted using keywords like mascara, eyeliner, eyeshadow, etc from twitter. I constructed a Tf-idf matrix (tweets x words) ...
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Interpreting results of Fuzzy C Means Clusters

I currently have the Fuzzy C Means clustering algorithm implemented in python and it works quite well. What can be said about the number of observations within each cluster? If each observation ...
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Minimum number of data points for clustering (Kmeans, DBSCAN, Isolation Forest) [duplicate]

I'm trying to do some clustering to find anomalies and the number of data points varies a lot (from 2 to 1000 data points), with two or four features. Is there a lower bound for the number of samples ...
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28 views

What is the technique to measure the performance of the methods clustering?

Given m, p and t non-zero natural numbers: m is the number of clustering methods, p is the number of internal measures for cluster validation (i.e halkidi, sd, calinski_harabaz, davies_bouldin...), t ...
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34 views

Stars and Machine Learning

Ok So I have been dying in interviews lately. Need to Brush up more. Maybe you can help me with this interview question (multiple Choice). If you tell me good sources to look at to learn more about ...
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Questionnaire - clustering of ordinal data

I have the following kind of results from a questionnaire. Here, are 4 questions(Q1-Q4) and 7 respondents. The respondents have scored with 3 the most likely event and 0 the least likely. ...
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Clustering timeseries subsequences (detection of modes)

I am working on a task that involves detecting different "clusters" of a timeseries signal. So basically I need to differentiate between "modes" (importantly, I do not know how many groups there will ...
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1answer
14 views

Expected Misclustering rate

I am reading this paper on minimax clustering error rates on high-dimensional Gaussian mixtures. The authors define a metric for expected misclustering rate as follows: For a two-component ...
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How to classify time series trends into 2 groups: “contain seasonality” and “doesn't contain seasonality”

I'm optimizing prediction model for time series data trends. Each trend may have seasonality effect or may not. I want to classify each trend into one of the following groups: "seasonality" or "no ...
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8 views

test for homogeneity and heterogeneity in clustering

I want to check if there is a way (or test) to verify homogeneity among and heterogeneity between clusters, besides the almost 30 clustering indices that are available (see NbClust). I am also aware ...
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Can I use the Silhouette to measure quality of clusters in different dimensions?

Can I use the Silhouette to measure quality of clusters in different dimensions? For example, let's say we run kmeans for some $k$ using 6 features of the dataset. Mark the resulted silhouette as $...
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creating new seurat object from cells of excitatory neuron clusters

I am very new to Seurat and coding in general, so sorry if this is a silly question (I don't see this exact question has been asked before). I have data from scRNA seq of DMSO and RO48. I completed ...
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Stepwise regression approach to clustering with “both” direction (merges and splits)

Classic approaches for clustering a set of points are either top-down or bottom-up. At high level: Top-down (or Divisive): you start with a single cluster, then split a single point or a bunch of ...
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multiple imputation for k-means clustering + outcome variables

I’m exploring whether distinct clusters can be derived from real-time, smartphone logs of daily social behaviors, and how these clusters predict self-reported depression and loneliness. My plan is to ...
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Cluster analysis: sign of relationships and weights of variables

i am running a cluster analysis and I have two questions. Do I need to make sure that all variables used to performance the cluster analysis have the same sign of the relationship? I can make an ...