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.

326 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
5
votes
2answers
148 views

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 ...
4
votes
1answer
197 views

Text classification based on n-grams and similarity

I have tried to cluster hundred texts using k-means clustering. I would like to consider other algorithms to group text based on their content and try to spot news not related to other news (topic ...
4
votes
2answers
98 views

KMeans clusterization on documents

Whether correct or not, I'm not able to judge being myself in the early days of the Data Science. However, I have applied a Kmeans on a corpus where some random documents (very short sentences) have ...
4
votes
0answers
95 views

Fixed-radius range search in non-Euclidean space

I'm trying to find an indexing data structure most suitable for my metric space: set of IP network related data (IP addresses, ports, TCP flags, ...), distance function is continuous, non-Euclidean ...
3
votes
0answers
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 ...
3
votes
1answer
72 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 ...
3
votes
1answer
88 views

PCA and k-means for categorical variables?

I have a clustering task at hand. The data that I have contains only categorical variables. So, k-modes seemed like the best option. But I am not sure what are the data pre processing steps required ...
3
votes
0answers
23 views

Visualizing the difference of a set of strings

I have a distance metric on a collection of strings on the order of tens of thousands. What would be an intuitive way to summarize how 'different' these strings are or when they overlap? My goal is, ...
3
votes
2answers
45 views

find most dense neighborhood of points in high dimensional space

I'm working on a project where I have many high-dimensional points and I want to find the most dense neighborhood of them. Ideally, out of my ~500 points that are each a 4x300 matrix (300 ms time ...
3
votes
1answer
197 views

What value can I gain by doing exploratory data analysis on features (and thus data) before doing clustering?

This might not be a very good question, but I would still ask if it's beneficial to do EDA before running a clustering algorithm? I understand that EDA helps us generate good and helpful insights ...
3
votes
2answers
539 views

Is k-means with Mahalanobis a valid option for clustering?

I want more info into if k-means with Mahalanobis distance is a mathematically/methodologically correct option for datasets with different variance clusters. The steps are: Create aggregate datasets (...
3
votes
1answer
28 views

Identify members who are likely to switch where they receive drug administration

I have access to medical claim data from a large health insurance company. As some of you may know there is a large delta between the price of drug X depending on where it is administered. My company ...
3
votes
0answers
50 views

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 ...
3
votes
2answers
905 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 ...
3
votes
2answers
242 views

Anomaly detection using clustering of highly correlated Categorical data

My data has two columns and both are highly correlated e.g. if column1 has value ABC, column2 should be XYZ i.e. ABC-->XYZ. If column2 has anything else its Anomaly. Likewise there are thousands of ...
3
votes
3answers
668 views

clustering 2-dimensional euclidean vectors - appropriate dissimilarity measure

I've got a set of approx. 50 000 2-dimensional euclidean vectors which are connected with 20 groups, i.e. each group has approx. 2500 2-dimensional euclidean vectors. My data includes endpoints ...
3
votes
0answers
159 views

Clustering with Replicator Neural Network

I'm trying to cluster an unknown set of data with a replicator neural network. The number of clusters is determined by the number of neuron units in the middle layer, multiplied by the number of steps ...
3
votes
1answer
107 views

Finding dominating attributes with in the clusters generated

I am having a dataset of customers where each customer is represented as some feature vector and I am applying K-means algorithm to this dataset. On the basis of those features, I can abstract and ...
2
votes
1answer
19 views

How to cluster texts by most relevant words

I have a huge amount of documents and every document has its own portrait, where a portrait has this structure (document_id, word, weight). TFIDF, basically. I want to cluster these documents into ...
2
votes
0answers
14 views

Methods of de-emphasizing some dimensions in a cluster analysis

I'm trying to understand how "weightings" on different dimensions in a cluster analysis might relate to the range of values along a given dimension in the dataset. DATA SET List of 1,000 to ...
2
votes
0answers
45 views

Clustering large set of images

I've got some big datasets of images (a few million each), and I would like to cluster them according to images' visual similarities. I've extracted a feature vector for each image; the space of ...
2
votes
1answer
136 views

Dendrogram: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

I am trying to plot a Dendrogram to cluster data but this error is stopping me. My datea is here. I first chose columns to work with: ...
2
votes
0answers
19 views

Resource-unintensive (low complexity) methods for large-scale unsupervised clustering?

I'm working on an issue where I need to cluster user types on a scale in an unsupervised manner. I've been looking at the basics like KNN and K-means etc., but I found it hard to scale, as these ...
2
votes
0answers
20 views

Deep Continious Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
2
votes
0answers
48 views

Classification and clustering of Time series data of temperature

I have a time series recorded data of temperature. This is what my data looks like: The change in data represents specific event or a class which I would like to detect when new incoming data. ...
2
votes
2answers
54 views

Using KNN to categorise inventory (physical stock items) - is it the best way?

I'm working on a machine learning problem involving inventory (i.e. physical retail stock), however through the cleaning (outlier removal) process some of the items (via their corresponding ...
2
votes
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 ...
2
votes
1answer
167 views

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

I have a dataset with 4 types of data columns: ...
2
votes
2answers
127 views

Techniques for Cluster Analysis of a Very Large (n=140000) Binary Dataset in Python?

In essence: what techniques in Python are possible to find clusters/trends in a very large categorical dataset? My very large dataset (140000 rows/observations, 80 variables) of categorical data has ...
2
votes
2answers
43 views

How to decide who to market? Clustering or Decision Tree?

I am working with a dataset that has enough observations and ~ 10 variables, half of the variables are numeric another half of the variables are categorical with 2-3 levels (demographics) one ID ...
2
votes
0answers
181 views

K-Means Clustering Profile Plot & Data Normalization

I am new to k-means clustering and I am working on a project on cryptoanalysis. I have a few questions and I hope to get some help here. I have four variables and my variables data values can range ...
2
votes
0answers
20 views

Assigning points to fitted planes

I’m working on a project involving fitting planes to 3D point clouds. The actual plane fitting part is working fine, but I’m trying to decide the best way to actually bound the fitted planes by the ...
2
votes
1answer
197 views

Customer Segmentation and Category association

I have to solve two questions on the following dataset: 1. arrange customers into mutually exclusive groups.explain the clusters. 2.identify 1-1 product category association rules for each cluster, i....
2
votes
0answers
128 views

Will flattening multivariate time series data before clustering make the results meaningless?

I have a large number of financial time series that I wish to do cluster analysis on. Each time series has the same length and spans multiple years of daily data (returns, volatility, etc.). As part ...
2
votes
0answers
56 views

News de duplication dataset

I am looking for a news dataset with semantically duplicate news articles tagged. Basically all the news articles which talk about the same story should be grouped. The stories can be worded ...
2
votes
1answer
30 views

How to retrain a K-Modes model based on daily data?

I have read that retraining a model depends highly on what you are trying to achieve. I am conscious that maybe I need to retrain my model daily and after a certain time I have to train the model ...
2
votes
1answer
35 views

Clustering Weekday Weekend Data and Multicollinearity

Hi I have data of weekday and weekend step counts in which I extracted metrics from them such as the wd steps, we steps, standard deviation of wd steps, standard deviation of we steps and so on... <...
2
votes
1answer
36 views

What's the good index to choose number of clusters so that obtained clusters are homogeneous?

I perform a clustering on one-dimensional dataset and I need a way to automatically decide what's the optimal number of clusters from $k \in \{2, 3, 4, 5, 6\}$. The number of observations to cluster ...
2
votes
1answer
42 views

Find shared properties of a cluster samples

I have a dataset which contains ~15 features. With the elbow method, I found out that the optimal number of clusters is probably four. Therefore, I applied the K-means algorithm with four clusters. ...
2
votes
1answer
33 views

Sensorfusion: Generate virtual sensor based on analysis of sensorsdata

I have a steam engine which is equipped with the following sensors: temperature sensor in the boiler room temperature sensor in the heating room pressure sensor in the boiler room rotations-per-...
2
votes
1answer
138 views

Clustering time series based on monotonic similarity

Context I am involved in a task of clustering 1500 time series of 500 observations into a few number of clusters. The time series share all the same observed property at different spatial locations, ...
2
votes
0answers
33 views

Measure of variety within list/cluster

I have a dataset of about 53000 points. It has been clustered twice, based on two sets of unrelated attributes. For the first clustering (clustering 1) I used DBScan, and it ended up with about 700 ...
2
votes
2answers
189 views

Grouping already clustered data (with a pre-defined x and y)

I have an already clustered data set (I wanna keep my x and y), where there's clearly a small group of elements in the middle that don't follow the expected patterns. I can select them manually, but ...
2
votes
0answers
118 views

how to extract the Top contributing labels/words in universal-sentence-encoder-large - TransformerModel?

I'm using the universal-sentence-encoder-large (Transformer Model) encoding process for embedding and then using the embedding for Clustering - Basically for unsupervised learning. I want to get the ...
2
votes
2answers
145 views

A suitable feature vector for images

I have a set of images of various products from different websites. I want to cluster the images based on the product shown in the image. How can I generate a suitable feature vector for an image for ...
2
votes
1answer
35 views

Identifying documents similar to specific clusters

Through performing clustering on a set of 1,000,000 text documents, I have identified 100 clusters. I am particularly interested in, say, 10 of the clusters. Imagine, I now have an additional set of ...
2
votes
0answers
243 views

Evaluating fuzzy C-Means clustering

I am new machine learning practitioner. I have run fuzzy c-means algorithm on a multi-label dataset (PPI dataset) on the network using skfuzzy python library. I want to evaluate the performance of the ...
2
votes
0answers
148 views

Clustering credit card accounts based on their balance trajectories

I am trying to cluster credit accounts based on the shape of their balance trajectories over the next 36 months, to identify the different types of shapes possible in the portfolio. Here is how I am ...
2
votes
0answers
27 views

Computing spectral gap of p-laplacian, p > 2

I'm looking for code allowing computation of the spectral gap of a graph p-laplacian with p > 2, i.e. the second largest eigenvalue. See http://www.ml.uni-saarland.de/code/pSpectralClustering/...
2
votes
0answers
162 views

Clustering events in a sequence.

I've a sequence of recurring events I want to group together into representing different operation activities of the underlying process. 1) These events might potentially have an order in their ...

1
2 3 4 5
7