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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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2answers
106 views

Is there a clustering algorithm which accepts some clusters as input and outputs some more clusters?

Heres the task: I have data I don't know much about. The final task is to build a classifier to classify the samples into a few categories. Some of the categories are pretty clear, we can easily use ...
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1answer
55 views

Is there a clustering algorithm that works with only pairwise distances as input?

My data are places for which I know all pairwise travel times (='distances'), and I want to cluster those places minimising the total pairwise travel time inside a cluster. K-means can't be used ...
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35 views

How to perform Anomaly Detection on a force profile?

I have a set of force profiles of an industrial machine. I'm trying to develop an algorithm that tries to understand when a new profile is "anomalous" with respect to the ones in "...
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1answer
54 views

How to cluster user historical data? [closed]

I have transactional-level users data that includes their behaviour, such as reading articles, searching for content, posting, etc. I would like to cluster (most probably K-Means) these users based on ...
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1answer
119 views

what is criterion in flcuster of scipy package?

Could some one explain what does criterion of fcluster indicate? I tried to read the documentation but I am unable to understand. What does maxclust criterion indicate?
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0answers
19 views

Recalculation the cluster centroids

I tried to cluster data points by k-medoids where k-centroids/medoids are randomly picked from (X), how those centroids are recalculated when there are some clusters changing by the updating x1? ...
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Resource-unintensive (low complexity) methods for large-scale unsupervised clustering?

I'm working on an issue where I need to cluster user types on a scale in an unsupervised manner. I've been looking at the basics like KNN and K-means etc., but I found it hard to scale, as these ...
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1answer
17 views

An algorithm for Automatic Tag Clustering [closed]

Out website dinf is somewhat like StackExchange: people are submitting small definitions of concepts. We would like to automatically assign those concepts into 'Topics'. The problem is that dinf by ...
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0answers
48 views

R: Cluster spatial polygons to bigger areas with attribute constraint of minimal population

Given the dataset with the spatial polygons below, I want to cluster these polygons to bigger areas, based on a similarity matrix. For the computation, I would like to use R. The polygons represent ...
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1answer
240 views

What is the correct formula for Jaccard coefficient with integer vectors?

I understand the Jaccard index is the number of elements in common divided by the total number of distinct elements. But it seems to be some discrepancy or terminology confusion about Jaccard being ...
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1answer
25 views

Should I perform customer segmentation before performing churn prediction?

Imagine a company with multiple lines of revenues coming from diferent products, but all customer can access these different products through the same account and the same online platform. My goal is ...
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0answers
20 views

Deep Continious Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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0answers
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How to find a 'similarity' measure between 2 pandas dataframes?

I have 2 pandas dataframes: one big (300.000+ rows) and one little (50- rows) with the same columns. Assuming that the entries of the little one form a cluster I want to identify the entries of the ...
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35 views

K-Medoid Clustering with Point Weights

I asked the same question at Cross Validated, here I implemented a K-Medoid clustering algorithm recently; I have a number of points $x_1, ..., x_n$ which have various properties and a distance ...
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1answer
46 views

Can we combine multiple K-Means Models as a single model?

I have a NLP problem statement where I use a Word2Vec embedding pre-trained model to convert key text to vectors and then on a set of terms run k-means clustering to get a final model for certain <...
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0answers
43 views

Why kmeans cluster breakup is like this [closed]

I have a galaxy spectrum data set (total 22000). Similar to an electronic wave data, two dimensional (Flux vs Wavelength). A typical set of wavelength plot looks like below Now I am doing kmeans on ...
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0answers
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How to get a KNN model (using quantiles to scale variables due to non-normal distributed data) to be better suited for non-extreme values in the data?

I want to cluster my data via k-means/modes. As the variables in my data are not normal distributed, I am not using the z-transformation to scale my data. I am scaling my data by categorizing each ...
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1answer
37 views

Ways of calculating the area of colored regions in a map

Background I am a PHD student trying to improve my data science. One of my research projects, has me tasked with determining the size of the clusters in a colored image of regions. Here is an example ...
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50 views

Clustering similar sequences using hidden markov model

I have several sequences of different lengths. For example, ...
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0answers
55 views

Visualization of transformed features in BERT

So I'm trying the Intent Recognition with BERT using Keras and TensorFlow 2 available at kdnuggets.com and this is the code for the results evaluation. ...
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1answer
25 views

How to apply multiple clustering algorithms to same dataset and make comparison?

I've a dataset and I want to implement K-Means, Fuzzy C Means, Gaussian Mixture Model, Spectral Graph. After that, I want to see the clusters that I get from different methods. What is the proper way ...
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0answers
18 views

how to use the hierarchical coefficients?

I am trying to understand whether I can use hierarchical coefficients obtained on different methods. I got agglomerative coefficients for methods like: "single", "complete", "...
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1answer
131 views

how to interpret a hierarchical clustering in the heatmap in the picture bellow?

I am trying to interpret the heatmap which was created based on a agglomerative hierarchical clustering. I am not sure what exactly the heatmap does, having in mind that I see on left hand side ...
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Classification and clustering of Time series data of temperature

I have a time series recorded data of temperature. This is what my data looks like: The change in data represents specific event or a class which I would like to detect when new incoming data. ...
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Is my data appropriate for Hierarchical Clustering?

I am a newbie in clustering and trying to check whether there are differences in Symptoms (example: cough, sneezing, shortness of breath, etc) reported across different comorbidity groups ( obesity, ...
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2answers
53 views

Looking for spatial clusters and anomalies. Is DBSCAN the right tool?

I have a regular 2D grid of data points (X, Y) with each point having a value. I'd like to identify clusters and then anomalies that don't belong to those clusters. I'm trying to understand the best ...
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1answer
20 views

Clusterize Spectrum

I have pandas table which contains data about different observations, each one was measured in different wavlength. These observsations are different than each other in the treatment they have gotten. ...
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0answers
162 views

Clustering time series data using dynamic time warping

I would like to cluster/group the curves in the attached picture with Python. The data is already normalized and my approach would be to use dtw (dynamic time warping) to calculate the distance and ...
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1answer
73 views

model selection in clustering

I am working on a mall customer segmentation dataset (5 features, 200 rows) using clustering. This dataset does not have any ground truth labels. I had a few doubts regarding clustering: Can I use ...
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1answer
15 views

From analysing their previos transactions how can I predict for what type of product is the customer more likely to take take an EMI

So basically I need a kind of product/ category affinity for EMI for all customers eg - Customer A is more likely to take an EMI on her insurance premium. One approach I had thought was to broadly ...
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1answer
36 views

Inference from text data without label or Target

I have a use case where I have text data entered by an approver while approving of some loan. I have to make some inferences as to what could be the reasons for approval using NLP. How should I go ...
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1answer
39 views

Identifying potential customers based on their Rank and Value

I have a dataset which has demographic data available for a list of new customers. the data does'nt include transaction data of the customers. I want to identify the top 100 potential customers among ...
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1answer
42 views

How to properly train your Self-Organized Map?

I recently stumbled upon the Self-Organized Map - an ANN architecture used to cluster high dimensional data - while simultaneously imposing a neighborhood structure on it. It is trained through a ...
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3answers
1k views

How to cluster and visualize 3D data in python

I have a 3D dataset of x,y,z points with 2 categories, category A and B. My end goal is to cluster all points in category B into volumes (spheroids/clouds) and find all points of category A close to ...
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1answer
31 views

Similarity matching between two distinct datasets (marketing case study)

I am working for a company that sells different products to customers. My objective is to find customers that are likely to purchase product X based on the profiles of customers that already purchased ...
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1answer
53 views

How can we identify potential customers for a new list of customers?

I have two data sets: Customer demographic data; Transaction data of the customers. Now, if I have to identify potential customers to develop a marketing strategy, I would make use of clustering to ...
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1answer
52 views

Clustering with categorical as well as numerical features

I have dataset consisting of house prices for example. The dataset contains features such as: house size, monthly rent, house colour, location, year the house was built. I wanted to group these all ...
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1answer
22 views

Different representations of dendrograms

I have a dendrogram represented in a format I don't understand: (K_5:1.000030e+00,((K_1:2.000000e-05,(K_2:1.000000e-05,K_3:1.000000e-05):1.000000e-05):1.000000e-05,K_4:3.000000e-05)0.806:1.000000e+00):...
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1answer
252 views

How to find farthest data points from a predefined cluster in a data set with Python?

I have a data set where certain rows are labeled as one class (and interpreted as distinct cluster #1 as such), but other points are either unlabeled or ambiguous. Hence I want to figure out which ...
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1answer
71 views

PCA for dimensionality reduction with simultaneous clustering

so, let's say I have a set of 3D points. Let's say these points lie more or less on a plane that is embedded in the 3d space, then I can use PCA to 'compress' these 3D points to 2D coordinates on that ...
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3answers
1k views

How to convert regression into classification?

So I have a regression problem with bunch of features X, and labels in the amount (price $). How can I convert it to classification problem? I have read about convert label from continuous to ...
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1answer
25 views

How to cluster government census data in order to group Metropolitan statistical areas

I have collected a bunch of census data from 2012 - 2018. I wanted to apply some clustering algorithms in order to compare Metropolitan statistical area (MSA's). Ideally once I run the clustering ...
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1answer
78 views

DBSCAN Clustering

I used K-means to get the number of clusters for my data(Elbow Method). Then I was trying to see if for some specific hyperparameters can we get the same number of clusters for DBSCAN. I tried Brute-...
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1answer
42 views

Why Davies-Bould chose a number ob cluster higher than Silhouette or Calinsky Harabasz?

I am doing use several metrics in order to know what number of clusters is correct in order to do this I selected 3 clustering algorithms and 3 internal evaluation metrics, Silhouette, Calinsky ...
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1answer
72 views

What criteria use in order to select the best internal validation for clustering?

I am doing homework about how to evaluate a clustering algorithm both hierarchical and partitional. For doing this I have a dataset that I can plot as you can see: The clustering algorithms that I am ...
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0answers
27 views

Elasticsearch for Data Science

can somebody recommend me any good resources on learning Elasticsearch for Data Science? I'm not interested in basics (how to query ES) but rather on books/tutorials on more advanced topics related to ...
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2answers
69 views

Using KNN to categorise inventory (physical stock items) - is it the best way?

I'm working on a machine learning problem involving inventory (i.e. physical retail stock), however through the cleaning (outlier removal) process some of the items (via their corresponding ...
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1answer
38 views

What is the most straightforward way to visualize color-coded clusters along with the cluster centers?

I have applied the kMeans Clustering algorithm to a dataframe and have gained cluster labels for each row. I had selected only two features. There are 4 clusters. I want to visualize the datapoints in ...
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1answer
49 views

How to compare two clustering solutions when their labelling differs

I am planning to test the reliability of a clustering approach for some data. My plan is to repeatedly (with replacement) draw a number of random subsample pairs (e.g. 2x 10% of the total data), run ...
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0answers
16 views

Identifying persistent clusters within a series of graphs

The task is to identify persistent clusters, i.e., groups of nodes that "persist" as clusters (tend to form a cluster) in a series of graphs. This is how I approached the problem: I form a ...

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