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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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How can I categoriese / classify a cluster of words?

I am just wondering if it is possible to classify word clusters? For example if I provide you an array of words [bird,chicken,dock,park,apple,grapes,furits,juice] ...
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A bit confused regarding clustering of users in a dataset

I have a dataset of book reviews: ...
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1answer
25 views

No target variable in my data

I have a list of transactions of bus route from place to place, I don't have any target variable here. I was asked to give meaningful insights from the data, what can I do here? I cleaned the data, ...
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using clustering for histograms

I have been assigned to find the frequency distribution of each individual column of a dataset using clusters specifically. I have no idea how to go about this, is it even possible to do clustering on ...
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1answer
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Preparing dataframe to carry k-means clustering [on hold]

Im trying to apply 3 different algorithms of clustering on my dataset. to check which one fits the best. I'm confused how should I convert my dataframe -k-means -DBSCAN -hierarchical clustering ...
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sklearn & Meanshift for NLP only returns 1 cluster

I am using sklearn.clustering to work with some text data and the MeanShift algorithm. I have: Done all standard NLP data prep like lemmatizing, removing stop ...
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Conditional Entropy and Mutual Information - Clustering evaluation

First of all, I am doing clustering and I have the true labels for my data. For evaluation, I am using the weighted average of the entropy values for each predicted cluster. I also came across with ...
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how to implement a hierarchical clustering technique using parallel execution in R

In R, currently to implement wards method for hierarchical clustering, I use the following code - results <- hclust(data, "ward.D2"). However as my data size has ...
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Random-Forest-based Similarity Matrix for clustering: how does it behave?

I am in the following context: Data: static, baseline health data at the patient level, 40 features, sparse (~ 25 binary features with many 0 or many 1 + other categorical features) Objective : to ...
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How to give a higher importance to certain features in a (k-means) clustering model?

I am clustering data with numeric and categorical variables. To process the categorical variables for the cluster model, I create dummy variables. However, I feel like this results in a higher ...
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How to analyze sets within Orange

Hi coming up with similar question like Q49352 - Clustering with sets as values . I am looking for the right way to work with sets in Orange. My set has a list of workflow steps from a workflow ...
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Is the mean shift algorithm adapted to my problem?

I'm currently building a model that can detect abnormalities in a timeserie. First, we predict the next steps and then we compare the prediction with what we measure in real time. We want to see if ...
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How to cluster text-based software requirements

I'm beginner in deep learning and I'd like to cluster text-based software requirements by themes (words similarities/frequency of words) using neural networks. Is there any example/tutorial/github ...
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graph based clustering with different attributes on vertices and edge proximity

I would like to apply a clustering based approach on a graph oriented problem where vertices do have a set of attributes in addition to another attribute on the edges. The vertices are people and ...
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Clustering for variables with large amount of categories

I have a dataset which, has variables with a lot of categories (some more than 1000). Since, large amount of categories effect the accuracy of the model. I saw some literature stating that if you do ...
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Why is my LOF algorithm producing the opposite result it should?

What could cause the local outlier factor (LOF) to output below 1.0 for outliers and above 1.0 for inliers? I have my code sort of working just by inverting the output, but I can't figure out what's ...
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2answers
59 views

Perform k-means clustering over multiple columns

I am trying to perform k-means clustering on multiple columns. My data set is composed of 4 numerical columns and 1 categorical column. I already researched previous questions but the answers are not ...
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19 views

Multiple correspondence analysis usage with K-modes

I plan to cluster a categorical survey data set with 30 questions (5 answer choices to each). I am a bit confused about whether MCA is really needed? I would be able to cluster using the K-modes ...
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Uniformly quantize the dependent variable into 4, 8, and 16 levels / R Programming

I have a question pertaining to the quantizing my dependent variable into 4, 8, and 16 levels. I will attempt to use kmeans to do this. Here is where I am lost. I need to perform these steps after I ...
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Orange Heatmap Clustering Linkage Type

Does anyone know which type of linkage is used in the Heatmap widget in Orange? From the previous question I can assume that it is hierarchical clustering, however, I have no clue which type of ...
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How to validate clusters after calculating Gower distances and Ward's clustering in R

I am trying to apply Ward's clustering on a mixed types dataset, and wanna explain what I did (maybe helpful to others), and I have some questions regarding this analysis, mainly how to validate my ...
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2answers
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How long would it take to become proficient in machine learning for someone with a non-statistical mathematical background?

I am currently a postdoc and my PhD was in applied mathematics in the area of numerical analysis and electromagnetic/acoustic wave propagation. There was no statistical element to my PhD, it was ...
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36 views

Clustering of multi-label data

The dataset consists of 1) a set of objects and 2) a set of labels, which are used to describe the objects. For the moment, for simplicity sake, each label can be marked as either true or false (...
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2answers
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Is there any clustering algorithm to find longest continuous subsequences?

I have data which contains access duration of some items. Example: t0~t5 is the access time duration, 1 means the items was accessed in the time duration, 0 means it wasn't. ...
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How do I identify clusters that match on categorical data?

I am seeking some directions for a proper path to research the solve for this problem: My company made all our employees take a "StrengthFinders" test, which results in every employee being assigned ...
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Using K-prototypes algorithm to cluster gdelt data by country

I want to cluster GDLET data by country using the k-prototypes algorithm. GDELT returns a list of themes as seen in this SE post. I was looking at the example data frame in this blog post as a ...
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Summary of Word cloud

I am clustering the bio of twitter followers using their bio description. After that I am trying to explain the different characteristics/separation of different clusters using the word cloud of ...
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Common cluster points between different runs

I am doing a Weka exercise using a dataset, and I'm supposed to do one run clustering with k means using 6 clusters, and another using 4. I have done this but I'm being asked to identify the number of ...
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1answer
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How to approach clustering of time-series with a single variable

Let me preface this by saying that I'm a complete beginner to R and data science in general, so my apologies if this is a rather trivial question. I do have a rough idea of what I would like to ...
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1answer
29 views

How to run AgglomerativeClustering on a big data in python?

I run AgglomerativeClustering on a sample of data and fit a model. then I decide to predict this fit for all of my data but I got MemoryError. How can I run ...
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1answer
48 views

Building a large distance matrix

I am trying to build a distance matrix for around 600,000 locations for which I have the latitudes and longitudes. I want to use this distance matrix for agglomerative clustering. Since this is a ...
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Are there any public datasets about mental health of patients containing physiological and psychological symptoms?

I would like to segment mental illnesses with clustering using machine learning. To do so I need training dataset which contains physiological and psychological symptoms of an subject. The closest ...
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1answer
54 views

Clustering based on distance between points [closed]

I am trying to cluster geographical locations in such a way that all the locations inside each cluster are at max within 25 miles of each other. For this, I am using Agglomerative clustering. I am ...
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2answers
51 views

Variable Importance in unsupervised anomaly detection algorithms

I am working on an anomaly detection problem to detect fraud in insurance claims. I have used the PyOD package and used algorithms like ABOD, CBLOF, Isolation Forest, and AutoEncoder. I couldn't find ...
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2answers
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Is it wrong if I cluster numerical attributes and categorical attributes separately?

I have a dataset of credit customers containing mixed data types (numerical and categorical with several levels). I am trying to perform segmentation so that I can end up with k groups and then build ...
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k modes: optimal k

I have categorical data and I'm trying to implement k-modes using the GitHub package available here. I am trying to create clusters in my (large) dataset of say, 5-7 records, each of most similar ...
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What does Make Density Based Clusterer in Weka do?

In Weka, there is a clustering algorithm with the name as Make Density Based Clusterer. When going through its properties, it takes a clusterer as base clusterer(I took it as K-means with k=3). It ...
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1answer
27 views

How to calculate a weighted Hierarchical clustering in Orange

I am doing my first cluster analysis with Orange (which I recently discovered and looks promising for this iterative and interactive process). Apparently, there are several methods of creating ...
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1answer
32 views

K-modes implementation in pyspark

I'm looking for an implementation of k-modes in pyspark. I found this and this as implementations. First, I tried implementing k-modes using the first link and faced issues. So I went ahead and tried ...
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1answer
25 views

Define value of a centroid

I want to choose a clustering algorithm for which I can define the value of centroids (and not only the number of them). Which algorithm should I look at? My understanding of k-means is that I can ...
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51 views

Best classification technique for following kind of data set

I have a large table where each record or row represents a single salesperson, and there are 50 columns or dimensions where each column represents one of 50 products potentially sold by any given ...
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1answer
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Cluster Analysis - Comparing Same Individuals Clustered Across Different Datasets with different features

I have an interesting problem, and I think my Google is failing me since I can't find the same problem anywhere. I have a set of individuals. I have 4 different datasets, with (some) to (all) of ...
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3answers
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Are there algorithms for clustering objects with pairwise distances, without computing all pairwise distances?

I'm looking for a clustering algorithm that clusters objects, by using their pairwise distances, without needing to calculate all pairwise distances. Normally pairwise clustering is done like this: (...
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1answer
59 views

Clustering by Distributions of Groups of observations

I have data as shown below. Like the groups shown A,B,C.. there are roughly 5400 groups of data and 15 observations for every group (I sampled 6-7 for each group and pasted them here). ...
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Extracting metrics from multiple classes of clustered objects

I am working on a project that involves using object detection over satellite imagery to identify (with bounding boxes) say $k$ different objects [houses, cars, farms, lakes, ...]. By considering the ...
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Clustering and graphing similarities of sentence subjects

I have a bunch of sentences. Each sentence is given a weight of how "close" it is to a particular subject. Ex. "I love reading math books" Subjects for the above sentence = ...
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Why in spectral clustering number of eigen vectors is same as number of clusters that we want?

In spectral clustering we take eigenvector corresponding to K smallest eigenvalues. Then we do K means clustering on these eigenvector to get final clusters. What will happen if we take different ...
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1answer
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Use output of K-Mean for Logistics regression

I've created a binary classifier using K Mean, which predicts fraud and legitimate accounts, 0 and 1. This uses two features, let's say, A and B. Now, I want to use other features like C and D, to ...
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1answer
29 views

Hierarchical Clustering and Variable Selection

I am using "Single linkage" hierarchical algorithm to cluster my data points with Gower Distance as my data have both qualitative and quantitative variables. After applying this for the full ...