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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1answer
36 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
37 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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1answer
26 views

A way to init sentence embedding for unsupervised text clustering, better than glove wordvec?

For unsupervised text clustering, the key thing is the init embedding for text. If we want to use deepcluster for text, the problem for text is how to get the init embedding from deep model. BERT can ...
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2answers
33 views

Clustering vs. Classification

I am a bit new to this, but I just had a quick question about clustering vs. classification. I have a bunch of texts that I want to classify. There are 4 classes I have at the moment, but texts can ...
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1answer
23 views

Correlation with Multi-Dimensional Clustering

I have a dataframe with multiple features, where I'm selecting 3 features to cluster on. Ex. ...
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16 views

How to determine the decrease of resolution in per cent necessary for a partly blurred frame to appear sharp?

Given is a frame of a video taken with a lens focussing on the background, so the foreground is slightly blurred. How to determine the decrease of resolution in per cent necessary for the blurred ...
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1answer
26 views

What's the complexity of HDBSCAN? [closed]

I can't find any complexity information about HDBSCAN by google or wiki. And how about compare to OPTICS?
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75 views

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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23 views

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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1answer
60 views

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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1answer
50 views

Clustering for Categorical Data? [duplicate]

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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4answers
75 views

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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1answer
50 views

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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1answer
33 views

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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1answer
22 views

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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1answer
32 views

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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0answers
17 views

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
235 views

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
84 views

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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3answers
48 views

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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1answer
54 views

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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0answers
9 views

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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1answer
39 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
22 views

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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1answer
70 views

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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2answers
33 views

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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2answers
38 views

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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1answer
47 views

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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0answers
22 views

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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3answers
238 views

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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2answers
43 views

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
271 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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1answer
37 views

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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2answers
13 views

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
24 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
28 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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1answer
134 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
65 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
151 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
29 views

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
30 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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4answers
127 views

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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2answers
30 views

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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2answers
40 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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0answers
21 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
59 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
39 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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1answer
19 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
26 views

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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