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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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9 views

Testing if a sample fits into an existing cluster

I have a sample of data I'd like to create a model from, which would create N clusters. After the fitting to clusters, I'd like to test various samples against the existing clusters, seeing if the ...
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Detect geolocation match a GeoJson pattern

I'm trying to detect if a geolocation (lat, lng) match a GeoJson pattern. As example i have line of location points and i want to detect if a new point can match that pattern in certain radius, like ...
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Looking for similar items in a large data set

I have a large database of people and I want to show a small number of people who are similar to each person in the database. So if one of the people was Wolfgang Mozart I would want to show Beethoven,...
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20 views

Clustering data using KMeans centroids of base period for pattern analysis

I have a data frame consisting of 12 months of Customer Transaction Level Data. The data is unsupervised. The data is divided into 6 sets of 2 months period each. Taking first period as the base, I am ...
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2answers
21 views

customer segmentation with unbalanced data

I am trying to do a customer segmentation on my transactional data and I am struggling a little bit on the best approach. Since it is an unsupervised model I can throw it to any algorithm and get some ...
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1answer
14 views

Efficient algorithm to find the lowest value cluster in a series of values

Let's say I have a list of numeric values that tend to be grouped into some number of clusters of values that are close to one another. I'm aware of things like k-means to group these into groups of ...
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1answer
16 views

Recommendation needed for unsupervised clustering on mixed data task

I have a task to perform unsupervised cluster analysis on mixed datatypes: images, physical and business measures – continuous and categorical. Businesswise: there are images of products and ...
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3answers
25 views

How to treat column with potentially meaningful NaNs

My data set has a column that indicates the time taken (in days) for members on a site - each with an ID - to sign up for an event. This can range between 1 to 300 days, with about half of the rows ...
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How To Do Cluster Analysis with a Categorical Index Column?

I have This DF : Amount_A Pos Code 0012 1251 10 0211 154 5 0321 35465 6 The Code Column is a category but i need it to do my ...
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28 views

Method for 'Simple' Clustering?

In a recent adult education class I took the prof shared a spreadsheet that was written in VBA code and takes ages to execute, I'm sure ...
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1answer
19 views

hierarchical clustering doesn't work as expected

I have a precomputed distance matrix. I'm trying to do an hierarchical clustering using scipy: ...
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1answer
32 views

How do you Show a Difference between Two Groups (Clustering)

I am approaching a data problem. My data set consists of observations of (X,Y) coordinates indicating a position on some grid. There are two groups based on a variable Z. Group A is all the points ...
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Choosing a distance metric and a clustering algorithm for time series

For every entity I have a corresponding time series which is built by a sliding window (win_size=7d, win_shift=3d, so we have overlapped windows) With every win-shift, we count how many users are ...
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1answer
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Cluster evolution over time

I have a dataset of transactional data with customer ID and I want to segment the dataset into groups using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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1answer
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Rank links from rss feed

I am trying to create a script to filter the most "intersting" articles from an rss feed and rank them. ...
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1answer
20 views

How to plot datasets 1 factors for K mean clustering python

I'm unable to plot the data for K mean clusering algo usingsklearn as it throws this error : TypeError: scatter() missing 1 required positional argument: 'y' Here is the function I have written to ...
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1answer
38 views

Apply a clustering algorithm on categorical data with features of multiple values [duplicate]

Let us I have a people data like gender, age, marital status, education, employment, hobbies. I want to make clusters of those people, having some similarity/common among them (for example they have ...
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2answers
61 views

Question about Similarity vs Dissimilarity Matrix

Right now, I'm working on a coming up with a similarity vs dissimilarity matrix for a set of data points for a clustering algorithm. My question is, if I want to use one of the many clustering ...
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2answers
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Question About Coming Up With Own Function for Distance Matrix (For Clustering)

Right now, I am currently working on implementing a clustering algorithm with millions data entries with regards to game users for a mobile game. A lot of the features I plan on using are unique to ...
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1answer
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Scaling of ordinal data before both hierarchical and KMeans clustering

I am new to data analytics. As part of my assignment I have to perform both hierarchical and Kmeans clustering on a data set wherein all applicable variables are ordinal (1-5 rating scale). Do I need ...
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14 views

Clustering in python when imbalanced data sets exist

I have a set of measurements with four features. Two features are continuous (time and distance) and two are discrete. We also know that the population consists of two groups. One is the minority ...
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How to tune / choose the preference parameter of AffinityPropagation?

I have large dictionary of "pairwise similarity matrixes" that would look like the following: similarity['group1']: ...
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1answer
27 views

Clustering stores based on weekly data

I have 1 year transaction level data aggregated at a weekly level for 1000 different stores. I want to cluster similar stores based on 8 variables such as sales, customer count etc. The concern is ...
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Setting up Zeppelin to work with a Spark Cluster

I have made a spark cluster containing 2 workers and 1 master. I followed the following link to set up the spark clusters. After successfully setting up the spark clusters I wanted to connect it to ...
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1answer
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what arguments should I pass to dbscan or optic in order to divid the data in a specific way

I have thousands of very similar data set that needs to be divided in diagonal way to two groups. for example: and I tried to play with the argument of dbscan and optic as eps and minPoints and even ...
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Is there a machine learning method to rank customers credibilty (goodness of a customer)?

I am working on a machine learning project that I want to rank each customer and put on a scale smt like one of those https://cdn1.vectorstock.com/i/1000x1000/90/40/credit-score-indicators-with-color-...
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3answers
36 views

Supervised clustering

I'm working on a clustering problem. I have a training set composed of sets of points where the clusters are known and I want to find the good clusters on a testing dataset. It's a kind of supervised ...
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1answer
39 views

How to validate a clustering model without a ground truth?

Im dealing with a dataset (text messages about source code comments) that are not labeled. I don't have a assumption about the implicits classes in this dataset. I want to discovery (by clustering) ...
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2answers
31 views

Categorical features preprocessing for clustering

Can anyone tell suggest the best practice for clustering data with mixtured features (both with categorical and continuous). I am struggling with a problem; I realized that for all metrics algorithms ...
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Clustering of very high dimensional data and large number of examples without losing info in dimensions

I'm trying to get a grasp on scalability of clustering algorithms, and have a toy example in mind. Let's say I have around a million or so songs from $50$ genres. Each song has characteristics - some ...
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How to remove noise using morphological filtering

I have two groups of dots that both contain noise between them: The line that separates the two groups in the picture is diagonal in shape. I tried to use morphological filtering on this image to ...
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How to calculate Fuzzy C-Means problem by hand

I figured that this doubt next can interest another students like me and help others also that are trying to understand mathematically the fuzzy c-means mathematical mechanism already that some books ...
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2answers
36 views

The actual results and results from pickle files are not matching in pandas for DBSCAN clustering

I've built a DBSCAN clustering model. The output result and the result after using the pickle files are not matching. Based on HD and MC column, I am clustering WT column. ...
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28 views

Clustering data by multiple values

I am trying to find a way to cluster/group students by their knowledge of different subjects. Given following as an example: ...
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1answer
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How would one get the HTML structure of a web page as a numeric vector? [closed]

Suppose you want to cluster, or classify, web pages inside a domain. In the same domain similar web pages always have the same structure more or less. (think of every product page an e-commerce would ...
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1answer
39 views

What is an appropriate machine learning technique to analyse development of status over time? [closed]

I have a dataset as follows (not the actual data, but representative): ...
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1answer
30 views

How to structure my data into features and targets for PCA on Big Data?

I want to apply the PCA algorithm from Scikit-Learn.(https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html ) At the part where I have to separate the features and the ...
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1answer
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Are DBSCAN and dbscan from the sklearn.cluster package different?

I'm new to DBSCAN. I was looking at a few examples online and came across a few instances where the following lines were used while importing the dbscan module: <...
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1answer
22 views

Suggestion on tag clustering visualization

I have a database of tags given by users to the product. For example user; product; tag 1; A; Tag1 1; A; Tag2 2; A; Tag1 2; B; Tag1 .. .. I am trying to cluster ...
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1answer
30 views

Unsupervised Clustering high dimentional data not having estimation for K

I have a dataset (all numerical) of 50K records containing 500 features. we are trying to find fingerprints. Meaning that we would like to cluster the data and report one of the nodes in each cluster ...
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1answer
32 views

trade offs between number of features with its score

I am running k-mean clustering on ~200000 samples. The dataset has in total 14 features. One feature is id and the rest are categorical. I have been playing with ...
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1answer
21 views

External cluster evaluation for a varying number of cluster

There are many external clustering indices like (Adjusted) mutual information, (Adjusted) Rand index, and many more. However, they are not very good at comparing clusterings where the number of ...
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33 views

Modifying BERT sentence encodings

I'm using BERT to encode sentences. The sentences I'm encoding are quite similar, meaning they all belong to the same overall topic. Therefor, I am using another parameter for measuring similarity. ...
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18 views

Clustering of Sparse Time Series

I have a dataset of certain user activity per week (e.g. purchasing an item or using a service per week) for the past 52 weeks and for 100K+ users. The matrix is very sparse (85% of the entries are ...
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1answer
112 views

Time series clustering using dynamic time warping and agglomerative clustering

I'm new to data science and I'm currently working on a project to classify electricity consumption profiles. This consists of electricity meter readings taken from sites on a half-hourly interval ...
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1answer
24 views

Clustering analysis for observations with lists as data

So I have several samples analyzed for their chemical composition. After data analysis, for each sample, I have a list of compounds found and their corresponding relative abundance. Some compounds are ...
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11 views

Neural network approaches for classification of time signals

I have 3D images that constitute of 2 spatial dimensions, e.g. (x,y) coordinates, with the 3rd dimension being a time signal. The signal is not periodical, but related to physical properties of medium ...
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1answer
29 views

Merging three different customer segmentation systems into one

I have been given a task where I have three existing customer segmentation systems (rule based e.g. if customer spends X in Y amount of time AND whatever then put in top spender segment is one segment,...
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1answer
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What is a color blob? Is it possible to use clustering algorithm to color blob detection problem?

Wiki gives this definition of blob detection In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, ...
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1answer
101 views

How to properly use approximate_predict() with HDBSCAN clusterer for text clustering (NLP)?

I have approached text clustering using HDBSCAN based on this article which describes how to do this in R. I've re-written this in Python using this library. The approach is to first calculate TF-IDF ...