All Questions
Tagged with k-means machine-learning
177 questions
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11
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Identify predictors for clustering output?
I have a dataset with variables collected years ago, and many variables collected this year as outcome variables. I want to combine all the variables collected this year to get one outcome, e.g. ...
- 43
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0
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19
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Clustering Mixed Data Types: Algorithm Selection, Distance Measurement, and Feature Weighting
I have a database of 74,000 records with 29 features. Fourteen of these features are categorical and are either 0 or 1, while the other 15 features are continuous and have been normalized and scaled ...
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0
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25
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calculation of the C-index clustering [duplicate]
Can anyone give me an example of working on the C-index clustering validity test, but calculating manually??
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3
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1
answer
28
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What is "clall" in index.Gap in "clusterSim" R package?
I am using the "clusterSim" package in my project (https://cran.r-project.org/web/packages/clusterSim/clusterSim.pdf, page 39) and I do not understand the meaning of the "clall" ...
- 51
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1
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20
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K means clustering of image with k=1 vs mean of all pixels
I have relatively uniformly colored images and I extracted colors using k-means. k means 1 showed the best results for my modeling purposes, k means 2 not so much, and with k-means 3 there ceased to ...
- 1
1
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2
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93
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Can I use K-Means to group customers based on a single variable?
I have a test dataset of 11m records. The dataset contains a global customer id and spend figure.
I need to group customers into the following categories:
0 Low
1 Low/Med
2 Med
3 Med/High
4 High
I ...
- 11
1
vote
1
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339
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Unsupervised learning: How to identify differences between clusters?
I'm learning about unsupervised learning and I tried to use KMeans, AgglomerativeClustering and DBSCAN on the same datase. The result was ok, they seems to work fine according silhouette_score() ...
1
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0
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48
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Can K-means put most of the noise in the same cluster?
I am working on clustering text data (very short sentences) vectorized with tf-idf. The data are characterized by high sparseness and the presence of abundant noise (considered here as documents that ...
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2
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2
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1k
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Time series clustering on large data
I am trying to do K-means clustering on my data which has time series length of 3700 and for (latitude,longitude) points of around 6000 in length. However, timeseries clustering using tslearn package ...
1
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1
answer
153
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If I convert continuous data into ordinal discrete data, but number of the class is 100(1 class per 1 percentile), can I say this is 'continuous'?
I have some continuous data, and want to do kmeans clustering with this.
But weirdly when I did kmean clustering with this data, the outcome was very conflicted with my presumption. So I decided to do ...
- 23
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28
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Regarding kmeans clustering, is it ok if I set the number of clusters just to get appropriate number of data of target cluster that I'm interested in?
For example, let me suppose that I have 100 thousands of geospatial data in my dataset, and I want to extract certain group that which is the most crucial. So I decided to do clustering and pick 'one ...
- 23
2
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2
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883
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Jenks Natural breaks - Interpreting Goodness of Variance Fit
I am trying to find breaks in a multiple continuous type variables.
So, I tried the jenks natural breaks algorithm.
Based on the code from here, I managed to find ...
- 3,342
1
vote
1
answer
60
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Does statistically simple algos qualify as AI algos?
We have a customer purchase transaction history data with variables like below
recency - how recently they bought?
frequency - How often they bought?
monetary - How much value did they bring to the ...
- 3,342
1
vote
1
answer
170
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Features differ between classes
Good evening everyone.
Regarding the topic related to Sparse Clustering (for example K-Means).
For example, in "Witten DM, Tibshirani R. A framework for feature selection in clustering" the ...
1
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0
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99
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Statistical method for finding homogeneous groups of curves
I need to divide a set of 100 or more response curves into groups.
These curves are formed by backscattering intensity along a range of frequencies. Basically, each curve represents the intensity in ...
- 11
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votes
1
answer
108
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Time Series clustering: clustering a dictionary of time series
I'm working on classifying times series to find clear pattern of use. My data is collected from clients of a telecom company, and we want to detect pattern of the amount of data consumed by clients ...
2
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1
answer
59
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Infer limits of unscaled values from their standardized values - Clustering
I am working on a clustering problem and I have some skewed variables.
So, I log transform them and use them in clustering.
However, instead of multivariate clustering, I do multiple univariate ...
- 3,342
2
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1
answer
116
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Converting unsupervised to supervised problem - Overfitting - bad?
I am working on a customer segmentation using 5 features such as recency, frequency, monetary, tenure, unique_product_cnt etc.
So, I did a RFM based segmentation where I used ...
- 3,342
1
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1
answer
377
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standardization/normalization for 1D clustering?
I have two input variables revenue and age. Am trying to find different bins within that variables.
For ex: I have ...
- 3,342
2
votes
1
answer
5k
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silhouette score vs Distortion score
I am working on segmenting my customers with clustering. My dataset size is 7315 rows and 30 features.
So, as a beginner to clustering, I passed all my 29 features (excluding id column) to the cluster....
- 3,342
2
votes
1
answer
104
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Why not link features instead of selecting them - Clustering
Currently, I am working on customer segmentation using their purchase data. I plan to use clustering techniques.
So, my data has below info for each customer (9 features and 1 id field)
Now I am ...
- 3,342
2
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1
answer
461
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Meaningful to retrieve original value after standardization using clustering
I already referred these posts here and here.
Currently, I am working on customer segmentation using their purchase data.
So, my data has below info for each customer
Based on the above linked posts ...
- 3,342
1
vote
1
answer
523
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RFM Customer segmentation - Why Avg monetary value instead of total monetary value?
I am trying to segment our customers based on their purchase data. And I came to know about the RFM technique (Recency, Frequency and Monetary) through these posts here, here etc.
Recency - How ...
- 3,342
2
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1
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599
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Confusion on why the value of SSE is lower when a cluster looks distorted on the plot
I have a dataset of shape (29088, 11). When I apply the Kmeans where K=2 I get the following plot:
Cluster C0 has 8554 points (in blue) and cluster C1 has 20534 ...
- 171
0
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0
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32
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K-Means clustering should cluster data evenly distributed or unevenly distributed? [duplicate]
I am clustering customers using their stay time on our web sites. When I only use one variable, time, for K-Means clustering with 10 clusters, customers look unevenly distributed to each clusters.
...
- 3,585
1
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0
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58
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K means clustering analysis to define geological facies using 2 attributes (ERT & seismic)
dear all.
Currently I am doing a project where the goal is to define geological facies of an area by using ML. The method that we are doing is k-means (we have no labels beforehand) and we are using ...
- 11
2
votes
1
answer
731
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Scaling a power law distribution for k-means clustering
For my project I want to group some products by using a few variables. For grouping, I am using k-means clustering. One of my variables is a metric called CR (conversion rate) which takes values ...
- 65
1
vote
1
answer
617
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Clustering data points with multiple rows
I have 100 people with their mobile browsing records, where each record tracks the person's browsing url and duration etc., and thus each person will have multiple rows of records.
Now I want to ...
- 353
0
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0
answers
64
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How to interpret result of kMeans scores if I have encoded the data with OneHotEncoder?
I am working on the AdventureWorks database and I have extracted some demographic data from the person scheme as follow. My aim ...
- 1
1
vote
0
answers
579
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Difference between Hamming Loss, Hamming Score, and Hamming Distance in multiclass multilabel classification
I am trying to understand the mathematical difference between, Hamming distance, Hamming Loss and Hamming score. I am trying to perform two actions
Multiclass multi label classification using SVM
K ...
1
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0
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134
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K-Means clustering technique for monthly data
I have an Unsupervised problem where user's Credit Card payment data is given for each month for various users for one year. One of the feature in the data having "User Id". For most of the ...
2
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0
answers
290
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Update centroids in minibatch K-Means
I wish to know about the operation of minibatch KMeans through a very simple algorithm. The aim of this post is to know how should one update centers in minibatch KMeans. I intend to integrate ...
- 121
2
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2
answers
72
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How to make clusters (consisting of demands) equal to the load of a truck?
I am working on a routing problem where I have thousands of points (places) with individual demands (in Weight and Volume).
So far I have created 5 clusters based on their location. Now I need to ...
- 200
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0
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78
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The total within sum of squares gradually decreases in K-means algorithm
Show that for K-means algorithm,
$ \sum_{k=1}^K \sum_{i \in C_k} d(X_i,\bar{X_k}) \ge \sum_{j=1}^K \sum_{i \in C_j^\prime} d(X_i,\bar{X_j^\prime})$,
where d is the squared Euclidean distance,$\bar{X_k}...
- 23
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0
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31
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What the difference between clustering methods?
I am focusing on a thesis for introducing clustering methods. Chapter 3 includes hierarchical clustering, partitional clustering and density-based clustering. Meanwhile, chapter 4 is mainly on Self-...
- 111
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1
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184
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The resulting image file is even larger than original when using K-means to do image compression
I am trying to compress jpeg file
[Original Picture]
[Compressed Picture with K-means using K=10]
However, the original one is 85K while the compressed one is 101K?
Here is the code I use:
...
- 11
1
vote
0
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172
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I don't understand why each time Kmeans finds the same centroid given different initialization?
The k-means algorithm does the following:
Given a set of points, we first choose k random points to be the initial centroids.
We then create k clusters. The ith cluster contains the points nearest to ...
- 11
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votes
1
answer
93
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Can K-means be used to group data in win/lose categorical values for prediction purposes?
Currently I have a dataset with matches played by a team against other teams. Some of the variables are: kills, deads, assists, amountgold, amountdamagedone, result(win/lose). What I want to do is ...
- 101
2
votes
1
answer
504
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Can the k-nearest neighbor algorithm tell you how many clusters there are among predictors?
I recently did a short course on machine learning in R and found the k-means and k-nearest neighbor techniques extremely interesting.
Forgive my naivete if this is all wrong, but it seems like the ...
- 2,187
1
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0
answers
50
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Precise definition of K-means
I am reading about K-means algorithm, and trying to explain it to myself in one sentence. However, I am a bit confused. I have came up with following definitions and I am not sure whether which one is ...
- 11
1
vote
1
answer
2k
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Confusion matrix for k-means algorithm
Using R, I ran the K-means algorithm on a dataset with 1m+ rows. Using elbow plot, the optimum no. of clusters was found to be 3. Now each data point is assigned a cluster from the set {1,2,3}. But I'...
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2
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1
answer
926
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Interpretation of Cluster Distortion on Normalized data
I have a clustering problem which I solved using KMeans clustering. I also know that the Elbow Method for cluster evaluation can be used to approximate a feasible pick for the number of clusters.
I ...
- 143
4
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0
answers
704
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Clustering text embeddings: TF-IDF + BERT Sentence Embeddings
I am trying to cluster a few thousand forum posts that are similar in content to Stackoverfow.
So far, I have tried two main approaches to represent the posts:
TF-IDF
Sentence embedding based on BERT....
- 61
0
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0
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254
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Classification on aggregate data
I've been tasked with creating a model that can classify individual cases as either something to be flagged or not. However, the training data I have access to is only aggregate data, where each row ...
0
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1
answer
125
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KNN and K-means, very different but possible equivalency?
Why does the k-nearest neighbor algorithm and k-means clustering algorithm with $k=1$ act the same?
- 13
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0
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36
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Is variable contribution to the top principal components a valid method to asses variable importance in a k-means clustering? [duplicate]
If the answer is no, could someone give a simple counterexample?
Thank you!
- 95
3
votes
1
answer
4k
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KMeans clustering - can inertia increase with number of clusters
I am doing kmeans clusters on sales data and i see that inertia increases for the initial increase in the number of clusters. Can you please explain why that happens?
I am doing Batched Kmeans for the ...
- 85
1
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1
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63
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K-Means Clustering for telecom customers behavioral usage
I am trying to run K-means clustering on a dataset of 100k records and 26 columns. My problem is in the visualization or plotting clusters part. Since I have several features, I couldn't specify the x ...
1
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1
answer
101
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How to identify distinct classes for classification problems?
I'm working with a dataset in which we've taken audio recordings of coral reef habitat from 3 different types: healthy, degraded and restored. From each recordings I have 13 different continous ...
- 73
1
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2
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196
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Is it possible to have same result for knn classifier and kmeans?
Could we achieve similar grouping or results for a set of data, if applied with either Knn and k-means
