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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What Clustering Method Should I Use?

My data is a group of 10 thousand points (each having an node location (x,y)) that are spread across a plane. They are also chromatically-colored based on their weight. I need to finalize a bayesian ...
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Multivariate Gaussian distribution - Covariance vs linear dependence

From prof. Andrew Ng's Multivariate Gaussian distribution lecture, covariance measures linear dependency between features, in which case we might use Multivariate Gaussian distribution with covariance ...
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First two principal components explain 100% variance of data set with 300 features

I am trying to do some analysis on my data set with PCA so I can effectively cluster it with kmeans. My preprocessed data is tokenized, filtered (stopwords, punctuation, etc.), POS tagged, and ...
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Clustering for Categorical Data?

How exactly does k-means clustering for categorical data work? I have a dataset which has several categorical features that can have 2,3,4,..,n values. I could one hot encode them, but I'm not sure if ...
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How to get model attributes in scikit learn (not hyper parameters)

How to get model attributes list (not hyper parameters passed to Estimator's class)? For ex: kmeans = KMeans(n_clusters=5) kmeans.fit(X) kmeans.labels_ how to ...
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3d plot for clustering

I'm working on a cluster analysis project and was trying out different ways to plot clusters to explain the differences between the clusters. I did plot the different clusters in 2D. Can you please ...
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PCA & Clustering Confusion

I have a question related to K-Means clustering and PCA. In my project, I have two target classes - 0 and 1- and I am trying to group the records that were predicted as 0 into 5 clusters. I am using ...
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max_iter hyper parameter in sklearn.cluster.MiniBatchKMeans

What is the significance of max_iter in sklearn.cluster.MiniBatchKMeans? Is this the maximum number of times partial_fit() can be executed on batches of data?
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Can the extent of variability within a dataset be reflected through clustering?

As an example: I need to compare the extent of variability amongst houses belonging to 4 different architectural eras - I want to see how different the houses are within each group and then compare ...
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Identify significant features in clustering results

I'm a student in Data Analysis, working on a data clustering exercise. Two clusters have been identified based on a dataset with 40 features. To interpret and label these clusters, I'm wondering if ...
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Understanding Mapper clustering

Is there a way to find the number of clusters in mapper.map? It is a module in kmapper.KeplerMapper. When I plot the graph ...
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1answer
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How to find slope of curve at certain points

how to find slope at certain points circled in blue in below curve ? Are these below 2 approaches valid ? though they give different results . How to automatically find the points where the slope ...
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1answer
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Choosing a distance metric and measuring similarity

I am trying to decide which particular algorithm would be most appropriate for my use-case. I have dataset of about 1000 physical buildings in a city with feature space such as location, distance, ...
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What kind of clustering would work better on such data? Would k-means work on such data?

I have a dataset where datapoints are more or less spread like this: What if I want to split the data in 2 data clusters, what would be a good choice? Would k-means work here? Thanks.
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Why Gaussian mixture model uses Expectation maximization instead of Gradient descent?

Why Gaussian mixture model uses Expectation maximization instead of Gradient descent? What other models uses Expectation maximization to find best optimal parameters instead of using gradient descent?
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what kind of distribution is followed by word and sentence vectors generated by TFIDF ,word2vec,glove,bert,flair?

what kind of distribution is followed by word or sentence embedding vectors generated by TFID or pretrained models like word2vec,glove,bert,flair ? is it continuous or discrete or any other ...
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Machine Learning Methods for Spatio-Temporal Output [closed]

Is there a machine learning method (NN variant?) specialized to output a value for giving spatio-temporal output? I know we can have the outputs of a NN to give x,y,z and t values, but I wanted to ...
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1answer
25 views

Clustering with imbalanced data and groups

I have a problem that is about identifying clusters of highly correlated items. I initially focused on building a model and features that put similar data items close to each other. The main challenge ...
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1answer
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Algorithm query for bank customer segmentation

I've been using k-means clustering for bank customer segmentation up until now and I'm looking to explore other clustering algorithms in the banking domain. Is it a good idea to use affinity ...
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Python Clustering : Best preprocessing and how to see cluster characteristics?

It seems I need your help yet again leadies and gents. I've been working on this dataset using Python, mostly sklearn stuff, trying different kinds of algorithms, like K-Means, some density based ...
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1answer
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Sentiment analysis of tweets (Train model on a labelled dataset and use on some other unlabelled data)

I have a huge amount of tweets on a particular topic say 'ABC' and the data is not labelled. I want to perform multi-class sentiment analysis of these tweets. I tried many unsupervised clustering ...
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Grouping pages in a pdf into logical documents

I have a PDF file(single training instance) which can contain many documents(multi-page) within it(invoices, different forms, emails). For e.g a single PDF instance may contain Page 1 - Overall Cover ...
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2answers
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How can I encode a 'Name' so that similar names are represented by vectors close in n-dimensional plane?

I want to encode names of people for similarity comparison between them such that a name like 'Sarah' is closer when represented in vector to a name like 'Sarah connor', something very similar to what ...
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Need suggestions on customer segmentation

I have been tasked with performing customer segmentation for a Business to business use case based on customer purchase history. Can experts provide me inputs on how do I proceed with customer ...
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What type of consideration can be made using clustering?

I am clustering my data to see how information look like and which group may be identified. Since clustering is an unsupervised algorithm, I cannot test the accuracy of the classification. So I was ...
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Best practices for avoiding spurious artifacts in image cluster detection / color quantization

I want to know whether there are some common best practices for unsupervised detection of clusters / colors in images, in order to avoid spurious artifacts. To understand what I mean by 'spurious', ...
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How to handle categorical features in K-means?

I am working on clustering algorithms. I am working with titanic dataset. It contains 6 categorical features. I used k-means algorithm on this dataset. I am using label encoding for categorical ...
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k-means and LDA for text classification: how to test accuracy?

I have many tweets that I would like classify based on their similarity. Unfortunately I am not quite familiar with text-classification and nlp, so I had to read a lot of documents before having an ...
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1answer
26 views

Choosing attributes for k-means clustering

The k-means clustering tries to minimize the within-cluster scatter and maximizing the distances between clusters. It does so on all attributes. I am learning about this method on several datasets. To ...
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Should you cluster before performing collaborative filtering?

So I am building a recommendation model using customer and product information. This will be done via implicit, that is, a customer has a product or not as we don't have rating information about ...
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1answer
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How can I determine how many signals there are in a mixture?

Let's say that I have 9 sensors arranged in a 3 by 3 grid. I have multiple objects which emit the same signal and move past the grid of sensors, which are picking up the signals. I have a CSV file ...
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1answer
21 views

How to explain the results from this kmeans?

I got the following results by using k-means algorithm. There are $10$ elements in Cluster $0$ and $3$ elements in Cluster $1$. Do you think it makes sense and it might be an acceptable result? How ...
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1answer
16 views

Clustering with k-means for text classification based on similarity

I have a column that contains all texts that I would like to cluster in order to find some patterns/similarity among each other. ...
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High qe (quantisation error) but low mqe(mean quantisation) error in SOM

I read that sometimes the qe (quantisation error) is high for an unit but it might have low mqe(mean quantisation error) in a Self Organising Map. What would this mean? My intuition is that if mqe is ...
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1answer
19 views

Clustering mixed data types - numeric, categorical, arrays, and text

I have a dataset with 4 types of data columns: ...
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1answer
24 views

How to get the probability/closeness of a sample belonging to a specific cluster?

I'm new to this so please let me know if my logic of comparing cosine similarity and k-means is incorrect I got a set of ...
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1answer
45 views

How do I predict a set of frequently bought items?

I have a dataset of retail transactions wherein different users buy certain items together. For example, a user A buys a toothpaste, a toothbrush and a floss at the same time, and a user B buys a ...
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1answer
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What methods are available to evaluate similarity between different clustering algorithms?

I am performing extensive customer segmentation analysis and so far implemented Gaussian Mixture Models, K-Means, and Hierarchical Clustering. For the most part, the algorithms agree on the structure ...
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1answer
19 views

How to group objects in different sized groups by their similarity score

Complete noob at this topic, so bear with me. I have a collection of objects and I can calculate similarity scores between each pair of objects. I've gone ahead and created a "similarity matrix" that ...
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Alternative means of clustering streams of incoming facial recognition data

I have a time-series dataset of incoming face data. Each data point is a facial-feature-vector of length 256 that represents the facial features of a person (it is generated by a modified RESNET). ...
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Calculating Median and Mode of numerical variables for different subgroups in R

I have customer call data and I want to get the median and mode for the call success rate for different subgroups. My variables are: Customer ID, Employment Status (Retired, Employed, Unemployed), ...
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32 views

Calculate regression coefficients for individuals (low sample size regression)?

Is there a way to calculate the regression coefficients for individuals instead of just a group resp. calculating regression coefficients for a very small sample size? Background My goal is to test ...
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How to group news by topics when they do not have labels

I have a dataset that includes 20000 news titles and 9 columns that are not relevant (boolean values) for labelling them. I have tried to extract top words using tokenizetion and tf-idf for n-grams. ...
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17 views

How may I may fit the cluster number while it is going to the outside of the X-axis and when visualizing clusters in two dimensions?

I am writing code for DBSCAN clustering. I find the eps value which is 0.12 with the help of ...
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4answers
49 views

Clusters: how to improve results for text classification

I am trying to classify texts using kmeans, TfidfVectorizer, PCA. However, it seems that many texts are not correctly classified as you can see: I have texts in cluster2 that should be in Cluster 0 or ...
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1answer
29 views

kMean clustering for recommendation

I have a file with 50000 rows from a library platform. Each individual row saves a user, and shows the order in which the user, has selected. The books could be from various categories (e.g. roman, ...
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Clustering products across different countries

I have a requirement wherein I have to identify the products to which a new product will be similar upon it's launch. I am thinking about clustering the products together. The problem is that the ...
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1answer
15 views

Using feature importance to decet latent variables and grouping

Is it possible to use feature importance from Random Forests (e.g. based on gini impurity) or other models to determine which features I can use to group the rows of my dataset homogeneously? For ...
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0answers
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clustering more than optimal k and Overfitting in k-means

In my data by using elbow method. i got optimal k to be 3. but , i clustered them into 5 clusters.and the patterns in the cluster are as i wanted them . But, does using k more than optimal k decreases ...
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Will one hot encoding / unbalanced columns cause bias to Clustering Analysis?

I'm wondering if having too many columns about one certain feature is gonna cause bias to the clustering analysis. For example, if my dataset has columns = ['incoming calls', 'outgoing calls', '...

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