Questions tagged [clustering]

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval etc.

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25 views

Clustering initialization

I'm running into a problem while working on clustering. I work on data with white Gaussian noise. All of the methods I have come across use some sort of random initialization to set up the mean and ...
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Clustering list of list of integers

I have ~100 sets of samples with integer IDs. For example, 3 of them could be: a = [0, 1, 3, 4, 6...] b = [1, 5, 9, 102...] c = [1, 7, 10, 42...] I am looking to ...
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KMeans clusterization on documents

Whether correct or not, I'm not able to judge being myself in the early days of the Data Science. However, I have applied a Kmeans on a corpus where some random documents (very short sentences) have ...
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Hierarchical Clustering on transaction data

Problem Statement: Let's say I have buyer transactional data for every product, features are categorical and numeric. I want to cluster purchases that have similar attributes in terms of who's ...
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6 views

Finding differences in smooth embedding spaces?

I'm trying to find statistically significant differences between embeddings (by an autoencoder) of different datasets. At first I tried to embed them separately, and cluster them. However, the ...
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21 views

Evaluation of multi-label clustering

I am trying to find some evaluation methods for multi-label clustering. I refer to this paper: Kai Tian, Meghan Revelle, and Denys Poshyvanyk: Using Latent Dirichlet Allocation for Automatic ...
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Transform skewed ratio data (value range from 0 to 1) to reduce the skew

I want data clusters. Because my cluster algorithm doesn't work with skewed data I want to change that in advance. I have ratio data, i mean probabilities (values between 0 and 1). But these data are ...
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1answer
8 views

Topic models for non-textual data?

I am looking to employ an unsupervised clustering on a dataset where each observation has a mix of textual and non-textual features. For each observation, I combine the features into a single vector ...
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3answers
321 views

clustering 2-dimensional euclidean vectors - appropriate dissimilarity measure

I've got a set of approx. 50 000 2-dimensional euclidean vectors which are connected with 20 groups, i.e. each group has approx. 2500 2-dimensional euclidean vectors. My data includes endpoints ...
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323 views

Clustering efficiency in a discrete time-series

Is it possible to identify the point in time where the cluster separation is at its most in a discrete time series clustering? Say I have 4 clusters of discrete time series and I want to pick a ...
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1answer
140 views

How to evaluate the K-Modes Clusters?

K-modes algorithm is available here I want to do clustering of my binary dataset. I need to specify the number of clusters that I need as an output: ...
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58 views

Clustering with groups in data related to cluster label

I want to predict which device got used in which room. Therefore I've got device and sensor data. My idea was to create a feature vector lie this: ...
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Testing if a sample fits into an existing cluster

I have a sample of data I'd like to create a model from, which would create N clusters. After the fitting to clusters, I'd like to test various samples against the existing clusters, seeing if the ...
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Number of attributes for clustering, SSE and silhouette [closed]

I am new to this site so please excuse me in advance if the question is not formulated correctly. My doubt is about what is a good combination of SSE and silhouette during the kmeans. I would also ...
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customer segmentation with unbalanced data

I am trying to do a customer segmentation on my transactional data and I am struggling a little bit on the best approach. Since it is an unsupervised model I can throw it to any algorithm and get some ...
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How to calculate performance and change train and test data size in MATLAB NNC Toolbox?

I used MATLAB Application toolbox for clustering but I don't know how to : Calculate performance and Error rate How to change test and train data size Script: ...
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Algorithm for segmentation of sequence data

I have a large sequence of vectors of length N. I need some unsupervised learning algorithm to divide these vectors into M segments. For example: K-means is not suitable, because it puts similar ...
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2answers
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How can autoencoders be used for clustering?

Suppose I have a set of time-domain signals with absolutely no labels. I want to cluster them in 2 or 3 classes. Autoencoders are unsupervised networks that learn to compress the inputs. So given an ...
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Remove noise by clustering on which step of pre-processing is better?

I am working on a classification task. The dataset is a UCI data set about machine learning with 200 observations and 2 classes. Part of my model includes the following preprocessing steps: remove ...
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3answers
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How to test accuracy of an unsupervised clustering model output?

I am trying to test how well my unsupervised K-Means clustering properly clusters my data. I have an unsupervised K-Means clustering model output (as shown in the first photo below) and then I ...
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29 views

How can I improve the results of my clustering

I am working on a project with the idea to cluster the sound waves of key strokes on a computer. So far what I have done was recorded about 50 keystrokes per key (only have done 1 - 10 so far), found ...
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Interpreting the C-Index

I have some problems understanding/interpreting the C-Index cluster quality measure. So, if we have $c(x_i, x_j) = 1 $ if $ x_i, x_j $ in the same cluster; $0$ else $\Gamma = \sum_ {i=1}^{n-1}\sum_ {...
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What is an appropriate statistical method for determining correlations between variables with likert scale data?

I am conducting an exploratory analysis with a dataset of about 200 records (all likert scales (numeric)). I aim to determine the correlations between the different variables that the responses ...
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1answer
53 views

Feature transformation possible at selected features or only at all?

I want to cluster. I have different features for that. Some features have a very small value range (from 0 to 0.8) and some have a very large value range (from 0 to 5 million). I want to use the ...
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Recommendation needed for unsupervised clustering on mixed data task

I have a task to perform unsupervised cluster analysis on mixed datatypes: images, physical and business measures – continuous and categorical. Businesswise: there are images of products and ...
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1answer
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Evaluate clustering by using decision tree unsupervised learning

I am trying to evaluate some clustering results that a company did for some data but they used an evaluation method for clustering that i have never seen before. So i would like to ask your opinion ...
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39 views

Labels are not given for multiclass classification problem

I have probably a weird question. If you are dealing with a multiclass classification problem, do you always have already determined target output/labels? I have e.g. a huge data set with a lot of ...
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1answer
57 views

Feature selection or Dimension reduction in unsupervised learning

I'm trying to do Embedded clustering using kmeans. This is customer data, so it involves a lot of sentences, so I'm using the universal sentence encoder before clustering. But I should be doing a ...
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how to handle outliers for clustering algorithms?

I am wondering what's the best way to handle outliers when using non-supervised clustering algorithms? Thanks!
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K-Means clustering for mixed numeric and categorical data

My data set contains a number of numeric attributes and one categorical. Say, NumericAttr1, NumericAttr2, ..., NumericAttrN, CategoricalAttr, where ...
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1answer
36 views

K-Means initialization

K-Means initializes the centroids randomly, but there are other methods to initialize. In this paper, http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf, they propose randomly choosing a data point ...
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3answers
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Aggregate categorical feature by the target

Having a list of triplets {X1,X2,Y} such as : {pennsylvania, fever , malaria} {pennsylvania, headache , malaria} {arizona, ketone smell , flu} {new york, fever , cancer} {ohio, hand pain , ...
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60 views

will k-means clustering converge to the same results given the same data set?

I did some study on the k-means clustering algorithm. It seems that the only non-deterministic part is the centroid - initialization. Assume I have 10k data points, and a given k. I then initialize ...
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1answer
34 views

What is the best to identify the proper hierarchy of this data?

So I worked on a hierarchical clustering algorithm to be able to determine which items are most similar, and what attributes are most important. I have two tables: Table 1: contains a bunch of item ...
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Why does changing the cluster number change the plot in Kmeans?

This might be a dumb questions but I can't find the answer to it. I don't have the perfect mathematical understanding of kmeans, so apologies if it is. I'm just wondering why I see a different plot ...
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Reduce drug spend using medical claims analytics

I have access to medical claims data from a US health insurance company. I believe there's an opportunity to find some cost savings by switching the site of service from high cost outpatient ...
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5answers
61 views

Detect geolocation match a GeoJson pattern

I'm trying to detect if a geolocation (lat, lng) match a GeoJson pattern. As example i have line of location points and i want to detect if a new point can match that pattern in certain radius, like ...
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Categorial Encoding with different cardinality

I have some user data for his data activities. Some examples of the columns are : Activity : ex. youtbube , viber, whatsapp etc etc. Cardinality > 1000 Region : Area identifier Cardinality > 10000 ...
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1answer
58 views

Stationary time series for clustering algorithms

I have a set of time series data that I would like to feed into a clustering algorithm (like k-means, using dynamic time warping as the distance function). After standardizing the data with mean 0 and ...
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2answers
35 views

Clearest way to visualise temporal data?

I've collected bus arrival times at my local bus stop from the past month - so I have every time my bus (a specific bus number) shows up at my bus stop for each day of the week (Monday, Tuesday, etc.)....
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31 views

Clustering categorical variable values based on continuous target values [closed]

Let's say I have $n$ data points with just one categorical feature $x$ and a continuous target variable $y$. I want to divide the possible values of $x$ into subsets such that the value of $y$ doesn't ...
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Tuning parameters in Affinity Propagation

I am doing Affinity Propagation clustering and trying to do tuning, but it takes time. A lot of time actually. As I am beginner I do not know how to get clusters. I need cluster numbers from 1 to 20 ...
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1answer
53 views

Clustering with custom criterion (minimum cluster weight)

Edit: following comment from @anony-mousse, I'm changing the question to search for a general clustering approach that matches this criterion (minimum weight per cluster). I am to use a clustering ...
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1answer
95 views

What is stored in heap structure in the following example?

I am planning to use heap structure to find the minimum distance between a set of 2D points and form a cluster.. and after to spend a couple of hours surfing on the internet, I have not still gotten a ...
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1answer
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Customer Segmentation: Should I use a variable, representing a product, that is unpopular in the dataset for K-Means Clustering?

I am working with a data set that, besides customer age and income, tells the balance a customer has in different type of bank accounts: Checking, Shares, Investment, Savings, Deposit, Mortgage, Loan, ...
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87 views

Clustering time series based on monotonic similarity

Context I am involved in a task of clustering 1500 time series of 500 observations into a few number of clusters. The time series share all the same observed property at different spatial locations, ...
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1answer
80 views

Clustering a set of vectors

Provided a set ($m$ no. of) of n-dimensional vectors what would be the correct unsupervised approach to cluster them? The vectors essentially represent patterns. For example: Set of vector is ...
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1answer
32 views

How do you Show a Difference between Two Groups (Clustering)

I am approaching a data problem. My data set consists of observations of (X,Y) coordinates indicating a position on some grid. There are two groups based on a variable Z. Group A is all the points ...
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5answers
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Best practical algorithm for sentence similarity

I have two sentences, S1 and S2, both which have a word count (usually) below 15. What are the most practically useful and successful (machine learning) algorithms, which are possibly easy to ...
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How to find vertical clusters in 1-D data

I have residuals of a multivariate time series data obtained from sensors on a server.spikes in the plots of residuals indicate abnormal server state. I want to cluster the data into vertical clusters ...