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Questions tagged [clustering]

Cluster analysis is the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors and/or cluster-samples should be tagged as such; do NOT use the "clustering" tag for them.]

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OPTICS Reachability Curve: Scikit-learn VS PyClustering implementations

I am comparing the Reachability curves generated by the OPTICS algorithm using the Scikit-learn (new implementation) VS the PyClustering one. The hyper parameters are not the same, but it seems that ...
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Clustering Algorithms- Sample Size

I have a small sample (290 observations) of categorical data and I am trying to decide on what clustering method to use. I am considering k-medoids, hierarchical clustering and Latent Class Clustering....
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How does non-uniqueness of data (aka duplicate data points) affect clustering?

I am trying to self-learn more about different clustering methods. I think I understand the main idea of the algorithms, but perhaps their use-cases can shed light on something that puzzles me - ...
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Method to identify recurring patterns (motifs) in a time series after giving a reference pattern

I would like to know if there exists an algorithm using which I would be able to extract repeating patterns from a time series dataset, provided I give it a reference shape. I have included an image ...
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Analysis on cluster change

I have 50 datasets each for every year from 1961 to 2010. These datasets keep data about GDP, mortality, natality, etc. My intent is to apply clustering for each dataset and then compare clusters. ...
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6 views

How do I prepare my data for sequence analysis in STATA? [on hold]

This is my first time performing sequence analysis, I want to come up with precarious employment trajectories, so I have already some variables prepared that measure in months when was a specific ...
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17 views

Gaussian mixture model (GMM) to cluster high dimensional dataset

My data set has ~20.000 dimensions. I want to use "Gaussian mixture model " to cluster them. To Construct mixtures, multivariate distributions are required. Given that high dimensionality, how ...
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19 views

Clustering on Financial Data [on hold]

I'm currently working on a project to apply machine learning (more specifically deep learning) methods to financial data. I want to cluster corporations according to a chosen feature. I'm familiar ...
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7 views

clustering applied to squared symmetric matrix [closed]

Edit as per @Peter Flom guidelines to write question: https://www.statisticalanalysisconsulting.com/how-to-ask-a-statistics-question/ problem: modelling topological properties of economics networks. ...
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1answer
94 views

How to determine number of profile in a dataset derivated from repeated measures?

I'm currently working on datasets which have been derivated from repeated measures over time (blood concentrations). Actually the descriptors of these datasets are descripting the shape of the curves (...
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1answer
12 views

Clustering users with very sparse data

I have a dataframe of the form ...
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1answer
9 views

clustering analysis\ data is in right skewed

what normalization technique(mean normalization/min max/zscore) is prefered to apply k-means clustering scope of data: right skewed variables are different scales & magnitude(days,counts) ...
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2answers
27 views

Clustering high dimensional data

I was going through this wiki page on clustering in high dimensions and I don't understand the following statement there. Can someone explain to me what this means? The concept of distance becomes ...
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7 views

What if an atribut in k-modes data have more than one mode [closed]

What if an atribut in k-modes data have more than one mode? Is it possible to choose all mode? Or maybe there is a theory to answer this?
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1answer
14 views

Weighted Minkowski distance for DBSCAN

I'm trying to make clustering of image's pixels with DBSCAN, using RGB values and pixel's coordinates as features. It works well with just RGB values as features, but I want pixels with the same color,...
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14 views

How to find groups inside the dataset (test for bi-multimodality)

I have non-normally distributed dataset, a record of a parameter, e. g. 50 subjects reacted to stimulation, (9 periods of time in total). So I have a matrix of 50x9 numbers, 9 medians for each time-...
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1answer
9 views

Invariance of K-medoids clustering under distance measure

Suppose we have n data points $X_1,X_2,...X_n$ where $X_i \in \mathbb{R^p}$ and we are performing k-medoids clustering to this dataset. Will the iterative (PAM) algorithm with identical initialization ...
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1answer
16 views

Clustering data with covariance for each point

I am looking to cluster data points that each have a covariance around itself (based on some function of its neighbourhood, but how I got it is not important). I would like to use the covariance to ...
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2answers
32 views

Name of this trivially simple clustering algorithm

Is there a name for the following (extremely simple) threshold-based clustering algorithm? It does a pass over the data and creates a new cluster when no previous cluster is within a given distance ...
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25 views

How do I divide a density/frequency plot?

I have a frequency plot, which is essentially a smooth histogram. There are three very clear features (divided with a line by eye). Please note, there are two groups, male and female. The data used to ...
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2answers
35 views

Machine Learning Algorithm for Count or Visit data

I am trying to figure out a good approach to use some machine learning on doctor appointment data. I want to first do an unsupervised clustering to look for any natural structure within the data (...
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Interpretation of NLP pipeline for topic discovery using gaussian mixture model clustering

I built a pipeline that does the following to discover topics out of a (very big: 50k docs per ~350 terms) Term Document Matrix: Compute the TfIdf score for each Term x Document pair; Rescale each ...
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1answer
35 views

K-means calculate MSE in Weka

I am doing some clustering analysis with Weka and decided to apply the k-means algorithm (the clusterer SimpleKMeans). On my first analysis I ran the algorithm with 2 clusters. Then, after finding ...
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2answers
54 views

Determining epsilon for DBSCAN

I'm using the method described in this paper for determining the optimal epsilon value for DBSCAN clustering in which a plot of the nearest neighbors is used: However, the plots in the paper and ...
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2answers
29 views

Initialization of Kmeans++ clusters

I would like to confirm the initialization steps of my K-means++ implementation (steps which chose initial centers of clusters). I am wondering if my initialization scheme has been implemented ...
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8 views

How to deal with categorical variables in a clustering problem? [duplicate]

I have a dataset with the following variables (among ohter variables) that represents custome card transactions and I'm trying to cluster the clusters using k-means. ...
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1answer
28 views

Determine clusters for the encodings of a Siamese Neural Network

I implemented a Siamese Neural Network that encodes images of different objects and outputs "coordinates" for each image in a lower dimension. My goal is to measure how good the network is clustering ...
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2answers
55 views

How to deal with one hot encoded variables in a clustering problem?

I'm using a dataset with customer card transactions to solve a clustering problem. On a first approach, I'm trying K-means using R packages ...
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1answer
24 views

Generation of synthetic data for Hierarchical clustering

I wanted to test various hierarchical clustering algorithms to check which algorithm performs best. For this, I was considering simulating some ground truth. Is the possible to generate a correlation ...
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2answers
29 views

R - high dimension data using k means clustering [closed]

The dataset is 1000(observations) x 700(variables), After using pca to do dimension reduction, PC150 explained 85% Variance, so I use this (1000 x 150) data to do k means clustering. This code was ...
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1answer
29 views

Hierarchical clustering for aggregrated features at higher thresholds/levels?

I am trying to use clustering on certain data. The data itself has three natural levels: at the lowest level the elements are fundamental building blocks, at the second level these fundamental ...
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1answer
11 views

K-means, Hierarchical, and DBSCAN clustering with feature value multiplied by constant?

I'm wondering if multiplying the feature values by 100 would have any impact on the clustering results of K-means, Hierarchical clustering, and DBSCAN clustering. Suppose I'm using Euclidean distance. ...
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0answers
23 views

Method to fit variable number of splines

If I have data that looks like below (independent observations), but the red and blue groups are unknown, is there a way to find the optimal number of curves (say, splines) to describe the data? In ...
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2answers
29 views

Unsupervised Clustering

My research is about comparing K-means and DBSCAN, and Im using unsupervised learning method in clustering. Is it true that the number of cluster in K-means is also the same number as the unique ...
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0answers
27 views

Principal component Analysis to Original variables [duplicate]

First, I have high dimensional data which has 3048 observation and 28 variables. Since I have high dimensional data I used principal component analysis to reduce the dimension of my data. Now I have ...
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1answer
23 views

How to select a single updated centroid if multiple centroids are equidistant for a single group when running k-means/k-medoids?

I am trying to write my own k-means and k-medoids clustering algorithms. I understand the general idea: given k centroids, one continually updates the centroids ...
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2answers
17 views

How to compare different clusterings of the same data

If I have two groups of clusters of the same data (e.g. that were created using different modalities), what's a standard/established way of discovering interdependencies/relationships between the two ...
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1answer
37 views

Aligning and clustering sequences of events

I have some data describing sequences of events. There are a number of different events (over 30), and the data records which event occurred in what order. There are no fixed number of events that ...
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1answer
20 views

How to use convolutions of pictures instead of FC layers? [closed]

How to use convolutions of pictures instead of FC layers? How can i do this effectively and efficiently.
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13 views

Is there a standard way to incorporate target continuous variable in DBSCAN, and use the model for inference?

I'm trying to use a density based clustering method on this data, where Y is the target variable Y and X is the independent variable (both are continuous): Snip 1 is hex-bin-plot of X and Y: So i am ...
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What type of clustering should be used to cluster survey respondents on a 1-5 scale?

Suppose I have a customer satisfaction survey with around 20 questions, asking customer's opinions on Company X. For each question and each company, the customer rates the company on a 1-5 scale, so ...
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2answers
36 views

Define attribute importance in unsupervised learning [closed]

I'm using 'NbClust' package to help me to get the "optimal number of clusters" and I noticed in my dataset I have attributes with different importance. I have 5 attributes: x1,x2,x3,x4,x5 and I know ...
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2answers
45 views

Alternative method to k-means that can be “guided” researcher's intuition? [closed]

I am trying to do a simple k-means clustering to my dataset. The result I get it the one that can be seen below: However, the result I would like to have, as it corresponds to geographical areas, ...
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Neighborless regions in hot-spot analysis -GeoDA

I am performing hot-spot analysis on aggregate data in the 632 districts of India. The hot-spot map produced by GeoDA software, using Queen's contiguity weight matrix identifies 5 districts as '...
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1answer
25 views

Hierarchical clustering in R

I have a dataset of around 25 observations and most of them being categorical. I have three questions for this. 1- Do the covariates I pick for hierarchical clustering matter or should I try and ...
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1answer
41 views

Is it okay to do ANOVA on group that is compared with itself and the rest?

I have 4 clusters that is obtained from clustering i.e. Group A, Group B, Group C, and ...
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1answer
14 views

Statistical test/method to create clusters or determine similarity between groups with many values for a single classifier

Situation: We are utilizing an application that transcribes phone calls into text and identifies when certain phrases (that we define) are said. We then enter logic for "categories" that use the ...
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14 views

Visualising sentence vectors by averaging word vectors

I have $82114$ sentences for which I have found the vector representation by summing over individual word vectors(using Word2Vec). Now I have a vector representation for each sentence in my dataset. ...
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0answers
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Clustering items based on response behavior on three tasks

I have a question and was hoping someone could point me in an appropriate direction. I conducted a large experiment and would now like to find patterns in the response behavior of the subjects. The ...
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2answers
79 views

In k-means clustering, why sum of squared errors (SSE) always decrease per iteration?

In k-means clustering, why sum of squared errors (SSE) always decrease per iteration? How can prove it by mathematical derivation of formulas? k : number of clusters m : number of examples $c_h$ : ...