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.

Filter by
Sorted by
Tagged with
1
vote
1answer
45 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 ...
0
votes
0answers
20 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', ...
1
vote
3answers
44 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 ...
0
votes
2answers
26 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 ...
1
vote
1answer
29 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 ...
2
votes
1answer
35 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 ...
1
vote
1answer
8 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 ...
-1
votes
1answer
22 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 ...
0
votes
1answer
20 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. ...
0
votes
0answers
9 views

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 ...
2
votes
1answer
27 views

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

I have a dataset with 4 types of data columns: ...
1
vote
1answer
28 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 ...
1
vote
1answer
53 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 ...
0
votes
1answer
16 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 ...
-1
votes
1answer
20 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 ...
4
votes
4answers
113 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). ...
0
votes
2answers
23 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), ...
1
vote
2answers
34 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 ...
1
vote
0answers
21 views

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. ...
0
votes
0answers
19 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 ...
0
votes
4answers
52 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 ...
0
votes
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, ...
0
votes
0answers
11 views

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 ...
1
vote
1answer
17 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 ...
1
vote
0answers
13 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 ...
1
vote
2answers
21 views

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', '...
0
votes
1answer
22 views

Should dimensionality reduction be done before k-means clustering if there are many features?

My data contains over 200 features and over 500 observations. I want to place the observations into a number of clusters based on the features that make them different. There are numerous ideas I ...
1
vote
0answers
14 views

Efficiently estimating the number of clusters in a dataset

Let's assume that I have a high-dimensional dataset and the true number of clusters is quite high (let's say 200 or 300). Are there ways to estimate this number efficiently? I am well aware of the ...
0
votes
0answers
15 views

Approaches For Recommender System Using Complicated Novel Dataset

I have a question about the best approach(s) I should take in building a recommender system for a project I'm working on. I have created a dataset. The dataset has the following: 400,000 users For ...
0
votes
1answer
26 views

Feature relevance in PCA + kmeans algorythm

Working on the World Happiness Report dataset, i have N countries with M features and a happiness score. This is the parameter I built 3 classes from: happy, medium, unhappy (numerical intervals of ...
0
votes
2answers
22 views

Clustering based on missing values

I have a dataframe of the form: ...
1
vote
1answer
17 views

What is the concept of Normalized Mutual Information in the evaluation of Clustering?

I know what mutual information basically is but not quite sure about why and how it is used in the context of evaluation of clustering mechanisms ? Can someone please explain the intuition behind it ? ...
1
vote
1answer
20 views

Text classification: accuracy [closed]

I would like to understand how to compute the accuracy of cluster analysis. I have hundred of texts. The dataset looks like as follows: ...
0
votes
2answers
41 views

Compute Accuracy of k-means [duplicate]

Could you please provide me an example of how I can compute the accuracy for a kmeans clustering? I split my dataset into train and test sets and computed the predicted clusters for the train set. ...
3
votes
1answer
35 views

Time Series Clustering

The thing that I am trying to do is the time series shapes classification. Basically the problem is as following: Let's say I have some time series and my goal is to have an algorithm that "finds" ...
2
votes
1answer
34 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 ...
0
votes
2answers
19 views

Scalable way to group users with similar titles purchased

I'm trying to figure out the best way to group customers based on checkout items in their shopping cart. I have the basket, and what's in the basket, but am at a complete loss on how to group all the ...
0
votes
0answers
22 views

k-means clustering

In my data, I have zero trade flows between some countries. I have latitude and longitude information and by using python, I converted them into the addresses. To handle zero trade flows problem, I ...
0
votes
1answer
27 views

Plotting clustered sentences in Python

I have the following three sentences, extracted from a dataframe. I would like to check the similarity and create clusters based on their level of similarity. ...
0
votes
0answers
5 views

spatially constrained multivariate clustering for demographics

What's the current methodology for clustering geospatial data by features? Example: I have some demographic dataset. Let's say this contains average home price and population density. So, an example ...
0
votes
0answers
42 views

Silhouette Coefficient Implementation in KModes Clustering

I have been trying to calculate the Silhouette coeffecient for the clusters I have created using KModes clustering (since all of my data fields are categorical). I am using matching dissimilarity as ...
-1
votes
1answer
17 views

Multi-Data Type Clustering

I have data with text, categorical, and numeric columns and would like to find a clustering algorithm that can handle all three of these data types. I am struggling to find a solution that would ...
0
votes
0answers
8 views

Good real dataset for comparing Tarjan and DBSCAN?

One method of determining "clusters" in a directed graph is Tarjan's algorithm, which finds all strongly connected components. Given a set of points in some space, equipped with a distance function, ...
0
votes
0answers
16 views

offering a basket of mixed goods to existing customers

We have a variety of around 500 types of products with low inventory and we are going to offer them on a discount sale to our existing customers. We also have the record of all goods sold in the past ...
0
votes
0answers
14 views

What interesting cluster analysis can be done on Covid-19 data?

I'd like to test my DBSCAN clustering algorithm on Covid-19 Data. I've thought about looking for clusters of countries using latitude, longitude, and # of cases, but this is a bit tricky. Is there ...
1
vote
2answers
32 views

Clustering on categorical attributes

I have a dataset with only 2 categorical attributes out of 9. How can I get a clustering analysis on it? I am using R. Do you have any advices about instructions, how to do it, topics, ...? here's my ...
0
votes
0answers
14 views

PCA and clustering, regression tree with categorical attributes using R

I am trying to analyze a dataset which has 7 categorical attributes out of 9. Can you please help me? I don't know how to find right instructions to do it. I only learnt how to do it with numeric-only ...
0
votes
0answers
9 views

learning pairwise similarity between signals based on apex alignment

Let say I have 3 signals as shown in the figure, I want to cluster them based on the idea that when the apexes of 2 or more signals align I consider them to be in a cluster. Therefore, applying this ...
1
vote
1answer
33 views

How to use a RBF kernel to create a “Kernel Space” using the similarity of each pair of point?

I am trying to use Semi-Unsupervised clustering using reinforcement learning following this paper. Assume I have n data-points each of which has d dimensions. I also have c pairwise constraints of ...
0
votes
0answers
12 views

Merging/Consolidation of duplicate records

I have large number of groups of duplicate records, which i need to merge to get a single master record per group. Input dataset contains columns like - FirstName, LastName, FullName, AddrLine1, City,...

1
2
3 4 5
21