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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Is Minimax Linkage a Lance-Williams hierarchical clustering?

I found the following article on "Hierarchical Clustering With Prototypes via Minimax Linkage". It is stated in Property 6 that Minimax linkage cannot be written using Lance–Williams updates. A ...
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2answers
2k views

Clustering or classifing n-gram-based text categories

I have large set of data records looking like this: "text", "category" I extract n-grams from text (2-, 3- and 4-grams) and store count of each n-gram per ...
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1answer
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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2answers
10k views

Multivariate Time-Series Clustering

I have a streaming data along with timestamp dataset that looks like this: 1.png Timestamp can be inclusive of "seconds" too, but the data may or may not change every second. it depends on the ...
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308 views

Clustering for high dimensional data

I am have a data set with 52 variables. Most of them have zeros, it resembles a sparse matrix. How can I cluster this kind of data and are there any special types of clustering? I am attaching pca ...
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86 views

Fixed-radius range search in non-Euclidean space

I'm trying to find an indexing data structure most suitable for my metric space: set of IP network related data (IP addresses, ports, TCP flags, ...), distance function is continuous, non-Euclidean ...
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2answers
47 views

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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0answers
74 views

Robustness of ML Model in question

While trying to emulate a ML model similar to the one described in this paper, I seemed to eventually get good clustering results on some sample data after a bit of tweaking. By "good" results, I mean ...
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1answer
200 views

Anomaly detection using clustering of highly correlated Categorical data

My data has two columns and both are highly correlated e.g. if column1 has value ABC, column2 should be XYZ i.e. ABC-->XYZ. If column2 has anything else its Anomaly. Likewise there are thousands of ...
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152 views

Clustering with Replicator Neural Network

I'm trying to cluster an unknown set of data with a replicator neural network. The number of clusters is determined by the number of neuron units in the middle layer, multiplied by the number of steps ...
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2answers
21 views

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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26 views

How to remove noise using morphological filtering

I have two groups of dots that both contain noise between them: The line that separates the two groups in the picture is diagonal in shape. I tried to use morphological filtering on this image to ...
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1answer
20 views

Find shared properties of a cluster samples

I have a dataset which contains ~15 features. With the elbow method, I found out that the optimal number of clusters is probably four. Therefore, I applied the K-means algorithm with four clusters. ...
2
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1answer
79 views

Clustering of Weekday Weekend Time Series Data

I have a dataset of the number of steps people take throughout a day over a period of months. I aggregated them so that each person will have an average weekday and weekend time series of steps. An ...
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2answers
45 views

Clustering of news combining headline and main article

I want to classify German police news articles and do an automated classification/clustering with regards to the kind of crime committed. Thus far I am not getting great results. Often times the ...
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1answer
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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25 views

Measure of variety within list/cluster

I have a dataset of about 53000 points. It has been clustered twice, based on two sets of unrelated attributes. For the first clustering (clustering 1) I used DBScan, and it ended up with about 700 ...
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2answers
143 views

Grouping already clustered data (with a pre-defined x and y)

I have an already clustered data set (I wanna keep my x and y), where there's clearly a small group of elements in the middle that don't follow the expected patterns. I can select them manually, but ...
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0answers
103 views

how to extract the Top contributing labels/words in universal-sentence-encoder-large - TransformerModel?

I'm using the universal-sentence-encoder-large (Transformer Model) encoding process for embedding and then using the embedding for Clustering - Basically for unsupervised learning. I want to get the ...
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1answer
27 views

Identifying documents similar to specific clusters

Through performing clustering on a set of 1,000,000 text documents, I have identified 100 clusters. I am particularly interested in, say, 10 of the clusters. Imagine, I now have an additional set of ...
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0answers
123 views

Clustering credit card accounts based on their balance trajectories

I am trying to cluster credit accounts based on the shape of their balance trajectories over the next 36 months, to identify the different types of shapes possible in the portfolio. Here is how I am ...
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0answers
23 views

Computing spectral gap of p-laplacian, p > 2

I'm looking for code allowing computation of the spectral gap of a graph p-laplacian with p > 2, i.e. the second largest eigenvalue. See http://www.ml.uni-saarland.de/code/pSpectralClustering/...
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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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150 views

Clustering events in a sequence.

I've a sequence of recurring events I want to group together into representing different operation activities of the underlying process. 1) These events might potentially have an order in their ...
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1answer
110 views

What is the name of this similarity distance metric?

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202 views

k- means clustering on Markov chain trasition probability

I have data set of 50 students. I want to cluster them on their sequential data ( While doing a job they followed multiple sequences A, B, c total 7 stages). I am planning to apply k-means clustering ...
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492 views

How do I choose number of clusters when Eigengap heuristic suggest 1 for spectral clustering?

Eigengap heuristic Method suggest number of clusters k is usually given by the value of k that maximizes the eigengap (difference between consecutive eigenvalues). I plotted the Eigenvalue ...
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1k views

t-SNE plotting DBSCAN clustering results very scattered issue

We are trying a DBSCAN clustering model on our 30,000 samples with 15 features each. We tuned the epsilon parameter small enough to make sure the radius of the clustering circle is small while it does ...
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930 views

How to choose the optimal k in k-protoypes?

To analyze a dataset from banking I have both numerical and categorical values. I transform them to analyze with k-prototypes. The original dataset: The modified dataset: E.g.: Job (for 1 to 12 '...
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580 views

Mixed geospatial and categorical clustering

I'm working on a project that seeks to identify clusters in urban development based on location (in lat/lon) and a categorical variable (what the particular site is zoned for). Ideally, the analysis ...
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0answers
447 views

Implement gaussian mixture model with stochastic variational inference

I am trying to implement Gaussian Mixture model with stochastic variational inference, following this paper. This is the pgm of Gaussian Mixture. According to the paper, the full algorithm of ...
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3answers
356 views

Clustering big data by reducing data accuracy?

I have 1 million rows with 20 attributes to do hierarchical clustering. When I want to build a distance matrix on this data by dist() in R, it says that it needs 5 ...
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0answers
475 views

graph database and its clustering

An undirected graph represents a database where nodes of the graph represent tables, edges represent the joiner columns. There are 100 databases( it means, 100 undirected graphs). We have to build ...
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78 views

Accept any suggestion to create training data from correlation matrix to find odd one out to identify difference in variation

I have N time varying feature vectors obtained by recording different parameters over time.This results in N*N similarity matrix which contains one to one correlations value for each feature. We need ...
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86 views

Selecting the number of hashes for minhash? Working with extremely sparse data and want more collisions

I'm attempting to use minhash to generate clusters and similarities, and I am primarily using ideas from these resources. http://www2007.org/papers/paper570.pdf https://chrisjmccormick.wordpress.com/...
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73 views

Finding dominating attributes with in the clusters generated

I am having a dataset of customers where each customer is represented as some feature vector and I am applying K-means algorithm to this dataset. On the basis of those features, I can abstract and ...
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33 views

How to apply K-Medoids in many CFG?

I am having around 1000 DAG(Directed Acyclic Graph) of different files showing java.io.BufferedReader usage. Following is representation of one of the graphs ...
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0answers
62 views

Spatial clustering of data points on a grid to obtain variable resolution map with constant statistical confidence

I have a grey valued image which is calculated as the mean of a series of images. The value of each pixel is therefore associated to a standard error. The pixel values and the relative standard error ...
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47 views

Discovering dis-associations between periods of time-series

I'm interested in discovering some kind of dis-associations between the periods of a time series based on its data, e.g., find some (unknown number of) periods where the data is not similar with the ...
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3answers
63 views

What best/correct algorithm/procedure to cluster a dataset with a lot 0's?

I'm new to statistics so sorry any major lack of knowledge in the topic, just doing a project for graduation. I'm trying to cluster a Health dataset containing Diseases(3456) and Symptoms(25) ...
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16 views

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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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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32 views

Method for 'Simple' Clustering?

In a recent adult education class I took the prof shared a spreadsheet that was written in VBA code and takes ages to execute, I'm sure ...
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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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13 views

Choosing a distance metric and a clustering algorithm for time series

For every entity I have a corresponding time series which is built by a sliding window (win_size=7d, win_shift=3d, so we have overlapped windows) With every win-shift, we count how many users are ...
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30 views

How to tune / choose the preference parameter of AffinityPropagation?

I have large dictionary of "pairwise similarity matrixes" that would look like the following: similarity['group1']: ...
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0answers
13 views

Clustering of very high dimensional data and large number of examples without losing info in dimensions

I'm trying to get a grasp on scalability of clustering algorithms, and have a toy example in mind. Let's say I have around a million or so songs from $50$ genres. Each song has characteristics - some ...
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30 views

Clustering data by multiple values

I am trying to find a way to cluster/group students by their knowledge of different subjects. Given following as an example: ...
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2answers
28 views

Identifying common keyphrase frequency in large dataset

I have a dataset of profiles which contain freeform text describing the work history of a number of individuals. I would like to attempt to identify frequently used words or groups of words across ...
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1answer
103 views

How can I adjust the legend when visualizing clusters in two dimensions?

How can I change the legend as we can see now the legend has some cluster numbers missing. How can I adjust the legend so that it can show all the cluster numbers (such as Cluster 1, Cluster 2 etc, no ...