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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5 views

Clustering with multiindex DataFrame

I have a huge amount of multiindexed data that, very simplified, looks like this: Code: ...
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Clustering on a graph with weighted edges

I have a graph with V nodes and E edges. Each edge e has a value -1 < e_v < +1, when -1 means these two nodes are VERY different and +1 means they are very similar. The graph is un-directed and ...
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Conceptual question about cosine similarity and clustering algorithms for word embeddings

Is the following statement true? https://stats.stackexchange.com/q/256778 The value of cosine similarity between two terms itself is not indicator whether they are similar or not. If yes then how is ...
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Which clustering model to use when doing market segmentation with survey data

We are looking to run a survey to determine the needs of our customers. For a needs-based segmentation model, can I run a variety of max-diff, multiple-choice, likert scale questions? Also, what type ...
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What's an appropriate clustering quality estimate / metric for precomputed distance in HDBSCAN?

HBDSCAN supports estimation of clusters from precomputed distances. However, the python implementation of HDBSCAN (scikit-contrib) doesn't create minimum spanning trees in the absence of raw data when ...
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Feature selection with KMeans Clustering

How can I select features for K-Means Clustering based on the silhouette score? I'm looking for something similar to Recursive Feature Elimination in Python, but for unsupervised learning.
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Finding attributes that make up dense clusters of fraudulent transactions

I have data about purchases customers made in my website. Some users later decline the purchase, a scenario I'd like to avoid. I have lots of data about the purchases made in my website, so I'd like ...
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Evaluate clustering labels using classification [closed]

I've clustered 500 documents into 7 groups using K-means. Is this reasonable to use classification models to evaluate the clustering model? What I would do is to get these 500 labelled documents using ...
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Why are the Order Of Initial Centroids effecting Kmeans Clustering?

For Iris Dataset I am doing the experiment. iris_k_mean_model_vor = KMeans(n_clusters=3, init=arr_4d) this is my model. Here I am feeding an Initial array of ...
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Clustering Ensemble or Consensus to combine the different cluster output

I tried to use ClusterEnsemble, getting error while using ClusterEnsemble package in Python: ...
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Online Generating Dendrograms with imported CSV file

Is there any website out there that performs hierarchical clustering on an imported file like CSV to generate dendrograms or similarity matrix? Free or paid does not matter. So far I found heatmapper....
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How to score different clusters of features for predictiveness?

I have a set of true/false data that represents whether or not a given feature was or was not active when the data snapshot was recorded. Data snapshots are recorded when the user takes an action. The ...
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clustering algorithms' evaluation [closed]

How can I show clustering performance of various clustering algorithms on various datasets using adjusted mutual information and adjusted rand index. for instance, the plot below .
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How to automatically cluster a set of parallel curves?

I have an ensemble of datasets, each one containing one or more parallel curves in a 2-dimensional domain. Each curve is formed by individual 2-dimensional points: What I want I am trying to ...
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How to treat demographic variables in clustering?

I'm working on a project to cluster franchises of a certain company. In this case, the dataset is grouped by city, so I'm basically clustering cities. I'm ending up with variables such as: Population:...
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FactoMineR: detecting dimensions with noises

I have some categorical datasets and was considering to do MCA using FactoMineR. Is there a way to detect dimensions with noises in FactoMineR? Considering to do a cluster analysis afterwards so it ...
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Training a Fuzzy Distance for Clustering later

I have a set of strings $ s_i \in S $ and associated labels $ y_i $, where $ y_i $ could possibly be null. There are many labels, but the cardinality is much smaller than the strings. $$ 1 << |\{...
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Looking for an algorithm to perform classification on multivariate grouped time series

I will be grateful for any help. I have multivariate time series, where every one of them has an unique ID. Also, there is a variable giving information about the trend type of the ID from a point of ...
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What algorithm to use to cluster data

I need to solve some business problem, but I am not 100% sure what algorithm to use as I did not master machine learning yet. I kind of think I has to be clustering, but I would like to get some ...
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Determining the optimal number of clusters by elbow method

I have a dataset that consists of 700 categorical columns and around 6000 rows. I created 2-50 clusters with the k-mode algorithm and plotted the cost function to determine the optimal number of ...
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Clustering without labels

I want to cluster the data points into 2 clusters. For that, I used a deep neural network but I have no labels to backpropagate. How can I backpropagate? which loss function I can use in this problem ...
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Combining two MCA before clustering

I have two kinds of data with several categories and multiple variables. I have done a MCA analysis on both of them to reduce the dimension. Now, would like to make a cluster analysis combining both ...
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Text clustering model on small dataset

Is there any way to run any clustering model on a small dataset with 290 text records (minimum character size is 100)?
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Clustering with Highly separable features

I noticed that in my dataset a particular column is highly separable where it splits the data perfectly into 5 distinct classes (re-evaluated where class2 means better than class1). I would like to ...
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How clustering is done with SVD

How can SVD be used for clustering? SVD results in 3 matrices. How are these matrices related to clustering? Can SVD alone be useful for clustering? Any kind of reference is helpful.
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One-hot-encoded variables dominating clustering

I am performing some unsupervised clustering with k-means on some transaction data that contains the following information: Customer units purchased in category_1 units purchased in category_1 time ...
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NMF and SVD clusters

Can we use NMF or SVD alone to cluster the data? I read that NMF and SVD are the relaxed forms of K-Means clustering. Is it possible to use NMF or SVD alone without any classical clustering algorithms?...
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Browser history segmentation

I'm trying to segment a browser history into semantically coherent sessions. For example, a user might be working on a school project for 30 minutes, then planning an upcoming vacation for 30 minutes, ...
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Is there any library to perform robust clustering given two probability distribution with noise?

Given a dataset $X$ consisted with $w|X|$ samples drawn from a mixture of multivariate Gaussian distributions (say in two dimensions) and $(1-w)|X|$ samples of noise, is there any ...
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Cluster Evaluation with Jaccard and Rand Index

I've clusterized my data according to 3 criteria in 3 groups. I used kmeans to obtain those cluster so the label for each cluster is random and changes at each script run. To evaluate the consistency ...
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Aggregating transactional data for customer segmentation

I have item-level transactional data where each row in the data represents a different item bought by a customer in a transaction (so if two different items were bought in the same transaction by the ...
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Encoding categories of items purchased for customer segmentation (clustering)

AIM: I am trying to deveop a model that will allow me to understand my customer better by clustering their purchase behaviour. CONTEXT: I have transaction level data that tells me, for a given ...
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Hamming distance between column-wise of two matrices

Is there any MATLAB trick to perform hamming distance between columns of two different binary matrices(-1 & 1): A(64 by100) and B(64 by 80), and report the minimum distances? "A" is a ...
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Tiering after clustering with Kmeans

I would like to have some suggestions on possible avenues that would make sense in the following context. 3 Optimal clusters have been identified in a 5000 list of customers using Kmeans Data model ...
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Clustering features of a class based upon the difference between features of a reference class and the particular class across multiple datasets?

I want to separate (generalized separation) the features of several classes based on the difference between the features (floating point values) of the particular class and a reference class across 7 ...
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Clustering new data with UMAP

I am trying to preprocess embeddings for a text classification model using 'all-mpnet-base-v2' sentence transformer. Initially, I used UMAP to reduce the dimensionality for visualization. Until I read ...
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sum of distances from N-points to set of other M-points in R

Imagine two related problems: I have one 2-dim data point and a set of $M$ 2-dim other data points. How to calculate sum of all distances between one point and those $M$ points? Result is one number. ...
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proximity matrix of random forest and data leakage

My objective is to train a random forest classifier on a binary set of data and use the resulting proximity matrix to understand the sub-populations in the data. I have read some papers on this ...
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High dimensional data: Tensorboard Alternatives

Tensorboars has a nice tool for the Visualisation of the high dimensional data. Is there any other libraries that allow to do fast clustering and Visualisation without thr need to install PyTorch or ...
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45 views

Global models for time series prediction with series of different lengths

As I haven't found much on the topic, I wanted to start the discussion about local- (iteratively for every column) vs. global models (only one iteration per forecast horizon, ex ante). As this is a ...
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How to divide numbers into different groups so that each group similar?

Basically, this is a problem of dividing the numbers into different groups based on similarity. ...
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Clustering algorithm for time series data with categorical dtypes

I have a large dataset with around 200 features, consisting mostly of timeseries and categorical data, with some continuous. The dataset is extracted from/by a postal service. Small example: Random (...
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Constrained clustering technique with an upper limit of weight

I need to cluster some points where each point has a pre-defined weight. I want to apply a constraint that the sum of weights of a cluster should not exceed an upper bound. Is there any technique (...
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1answer
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ggplot2 for Cluster analysis (non-readible row names)

I have made a cluster analysis and ended up with dendrogram; however the row names are not readible (made a red rectangle). May I ask if there is way to adjust it? ...
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1answer
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How to combine binary classification with patient stratification?

I am working on a binary classification model (healthy/diseased) based on gene expression data of different patients. As a second task, I would like to stratify these patients and find subgroups. I ...
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1answer
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Understanding hierarchical clustering features importance

I made a hierarchical clustering with scikit : selected_model = AgglomerativeClustering(n_clusters=8) hierarchical_clustering8 = selected_model.fit_predict(answers) ...
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Determining the effect of combinations of independent variables (customer charateristics) on dependent variables (customer value)

I have lots of transactional and demographic (etc.) data about my customers and I want to understand: "What are the characteristics (age, profession etc.) of valuable customers?" To do this ...
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I want to apply Time Series Clustering to time series data consisting on: Level & Growth, but I have only found algorithms for one series

Is there any implementation of Time Series Clustering which allows me to segment using two or more series of the same phenomenon both as input for the algorithm? Suppose I have $A_{i,t}=X_{i,t}$ and $...
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When use standardization, normalization or both?

I have a dataset with variables with different scales as shown in the figure below. I need to group individuals together and I'm testing algorithms like Kmeans and DBScan. In all tests I'm extracting ...
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Find most important and least important features for clustering algorithm

I am experimenting with clustering algorithms, like K-Means. Right now, I use all variables as input for the clustering algorithm. I am wondering if it is appropriate to do feature selection for ...

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