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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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How do unsupervised credit scoring models that don't consider historical financial data work?

There seems to be a number of startups (Zest Finance, Credolab etc.) that provide credit scoring schemes that rely exclusively on alternative data without considering users historical financial data ...
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17 views

Comparing learnt features in deep learning

What is the standard practice to compare learnt features for different deep learning features quantitatively. These features would be used to score similarity between the items. E.g. I use different ...
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13 views

Clustering circles with different radii with Gaussian Mixture Models

I am interested in clustering $N$ circles in the plane with varying radii using a Gaussian mixture model. The radius of each circle is an integer number $R_i\in\mathbb{N}$ determined from observation. ...
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14 views

Clustering data with equally sized clusters

I'm looking for an algorithm that can cluster data as accurately as possible (no need to be perfect) but with equally sized clusters (+ or - 1 element). I've been reading this article where it is said ...
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8 views

What are the advantages of Louvain method versus K-means for clustering sparse data?

I would like to better understand the strengths of the Louvain method versus K-means for high-dimensional sparse data (e.g. zero-inflated negative binomial gene expression counts or natural language ...
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33 views

Indications about the population when PCA essentially “fails” to reduce dimentionality

This is more of a conceptual question rather than a methodological one I guess. Let's assume that we have a dataset coming from a questionnaire and after some feature scaling we run a PCA to reduce ...
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5 views

How to inform the space and time complexity of K-means, SOM and Hierachical clustering

In the paper I am writing, one of the reviewers asked for an "a simple computational complexity analysis or time computational demands of their method" My question is : Can I simply report the ...
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1answer
20 views

Searching for the correct approach

I'm writing my Bachelor Thesis within the field of neural networks and I need some preparation of the data I'm using. Do you have an idea how I am able to identify the four levels in this graph via ...
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15 views

Use PCA in order to show impact of variables on clusters

I did a clustering of selected variables. Is it possible to use the PCA (contribution, correlation) in order to show the impact of each variable in the clustering? (cfr. image 1) and add complementary ...
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7 views

Find typologies within population [closed]

I think I screwed up my master thesis with a bad questionnaire. I have a total of 21 Likert statements which are in one big pile and not really sorted. I also have various nominal questions. I would ...
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18 views

Standard methods for comparing layouts [closed]

Following image contains two graphs I'm trying to compare. These are undirectional graphs. Both graphs have the same nodes (number of nodes and type of nodes), same connections and are laid out in the ...
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1answer
32 views

clustering with KL divergence

Recently I read some papers which related to clustering. The paper is https://xifengguo.github.io/papers/ICONIP17-DCEC.pdf In this paper, they calculate Loss function as KL Divergence, KL(P||Q). ...
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36 views

How does Google Photos face recognition use user-provided labels?

I'm working on a toy project which I think is analogous to the problem of detecting faces and assigning names to them in Google Photos, so I've been thinking about how that process might work. From a ...
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1answer
11 views

How bregman divergence gives optimal solution for cluster assignment?

Can somebody gives intuition behind Bregman divergences that how using it leads to optimal cluster representation? And why using ...
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0answers
11 views

How do I get intervals classes (groups) from a histogram of data?

in my problem setting, I have data for 1 variable. The data is numerical, and in my problem setting, I just generate a frequency count of the data, for example: If data is: I create a frecuency ...
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15 views

How to find modes of multivariate time series dataset [closed]

I have a dataset of different multivariate time series (with features $x_0, y_0, x_1, y_1$ that are coordinates of starting and ending point of an event within each time series' observation. The data ...
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17 views

Hierarchical clustering: Should I first normalize / correct for phenotypic data?

I've a set of N=100 samples, each sample having M=10 variables (100x10 matrix). These 10 variables (M_i) are responses to some drugs. In addition I've for each sample a list of phenotype data (...
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8 views

Typo in the definition of Finite Mixed Model in Machine Learning a probabilistic Perspective

In subsection 25.2.1 it's stated, regarding finite mixture model: The usual representation (of a finite mixture model) is as follows: $p(x_i|z_i = k, \boldsymbol\theta) = p(x_i|\boldsymbol\...
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16 views

Inferring GMM parameters with Gibbs Sampling

On my book, "Machine Learning A Probabilistic Approach". It's stated that is straightforward to derive a Gibbs sampling algorithm to fit a mixture model, especially if we use conjugate priors. So ...
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1answer
14 views

jaccard distance if one samples is a subset

I have a very basic question but I cannot find an answer (especially for a clustering situation). I am trying to do hierarchical clustering of samples using jaccard distances. One sample contains ...
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0answers
25 views

Understanding short animation about Dirichlet Process Mixture Model

On the wikipedia page of Dirichlet Process, there is the following video. I don't get the point of the video. My first impression was that the video was showing the fitting of one-dimensional data ...
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24 views

Network clustering based on factor scores

I have a clustering problem for the following data (sample from the original): ...
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1answer
59 views

Do GEE and GLM estimate the same coefficients?

In a GLM, the likelihood equations depend on the assumed distribution only through the mean and the variance. The likelihood equations are $$\sum_i^n (\frac{\partial \mu_i}{\partial \eta_i}) \frac{...
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1answer
27 views

How do I evaluate/validate my encoding technique?

I have log data and I encode the data for clustering purpose. For example, I have one data column and I represent this unique data in numerical values or binary to be as one column as below. Example ...
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1answer
23 views

Clustering Algorithm for for Different types of dimension

I want to cluster radar data but using its position (x,y) and its radial velocity. As position parameters have same units (meter) but radial velocity is in m/s. Which algorithm can be used for such ...
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1answer
49 views

'p-value' for clustering

I was just wondering if there is a way to check if the clustering found by a specific method (e.g., KMeans, DBSCAN, Mixture Models, ...) is significant. Something in line with, there is 5% chance that ...
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10 views

Multi variable clustering cartographical data

Firstly , my knowledge in statistics is very limited , so excuse me if I'm ask a none well placed question. I have a country ,( example : USA ) , and i have 3 set of data 1) position (lat , lng ) ...
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1answer
36 views

Normalizing vs Scaling before PCA

I know there's a lot of content about PCA pre-processing, but I am still somewhat confused. I have a dataset that contains some clear patterns: 1 variable is whether a person has financial resources (...
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17 views

Can I use regression output to feed my clustering algorithm?

I'm working on this example: e-commerce dataset with purchases made by users as well as minimal demographic data like age and gender. The age field is rarely filled. So I want to use regression to ...
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1answer
21 views

Can I view the features of my clusters without doing it by hand?

I have performed hierarchical clustering on a data set with 186 participants and 94 variables for each participant. What I want to know is if there is a way to see which features are "driving" my ...
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1answer
19 views

Group events based on start time and duration

I have a data that look like: ...
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1answer
15 views

Subjectivity clustering process

While studying about clustering (newbie to the field) I have seen many times the term 'Subjectivity'. Can someone explain me what exactly this term means? is Subjectivity always present in the ...
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1answer
26 views

Quality of PAM clustering

I have a mixed data and I have been searching for the best method to cluster it and I've chosen PAM. I am working btw with R. I've considered all the 17 variables of my data to cluster: 4 qualitative ...
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13 views

Sampling methods - Stratified Vs. Probability Proportionate to Size Cluster

India has 29 States, each of which is further sub-divided into smaller administrative Districts of varying size and population. I need to download micro (firm-level) data from each state, but I do not ...
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14 views

How is the upper bound for Normalized Mutual Information determined?

Mutual information between two clusterings $A$ and $B$ can be calculated as: $$MI(A,B)=H(A)+H(B)-H(A,B)$$ In the 10th page of this paper it is stated that $MI(A,B)$ can vary in the range $[0,\min\{H(...
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28 views

Testing Randomness in day of year values

I have airline booking data (no. of bookings vs day of year). Day of year is a vector, taking values from 1 to 365, with stepwise increments of 1. We can have one data-set where booking exists for ...
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1answer
26 views

Algorithms for Graphs Clustering

Which methods is available for graph clustering? The most information by query "Graph clustering" concentrated on the finding set of nodes in the one large graph (or graph partition), but it isn't my ...
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1answer
37 views

R: Statistical tests for cluster analysis?

I'm not even sure if this is a well-formed question, but here it goes: Let's say I have three variables (shape, size, and color), and I want to test whether those three dimensions describe uniquely ...
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4 views

Clustered or blocked? Running power analysis for DIM

I am working with the following design: -80 districts, each district paired using matching and half assigned to T1 and the other to C1 -All sub-districts within a district (let's say 10) receive T--> ...
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2answers
56 views

How to compare different clusterings?

In an 'unguided' experiment, we asked several people to make groups with a defined number of objects presented to them. They were free to do as many classes as they wanted, and to choose their names, ...
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1answer
20 views

Clustering objects into groups

Clustering is partitioning of $n$ objects into some number $k$ of groups. I am looking for a theorem to the effect that any such clustering is plausible. I am sure I once saw such a theorem, but I ...
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1answer
15 views

How to cluster a (directional) dissimilarity matrix with both positive and negative values?

I may be thinking of this incorrectly but what would be the best way to cluster a dissimilarity measure that has direction? For example, if someone had condition A ...
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1answer
97 views

Scikit-Learn Gaussian Mixture: How can log-probabilities be positive? [closed]

I am fitting a Gaussian Mixture model: gm = GaussianMixture(n_components=K) gm.fit(features) When I do: ...
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0answers
8 views

Which is the best strategy for clustering a glossary of terms by exploiting their definitions

I have a glossary (dictionary) of terms together with short definitions (1 to 20 words). I want to cluster these terms by their application domains by using their definitions; for example, clustering ...
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1answer
25 views

Duplicated Rows in Mixed Data Type Clustering

I have a dataset which has ~200k rows and looks like the following - ...
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1answer
56 views

Spectral Clustering of a skipgram model

I have a model where I'm applying Spectral Clustering to frequencies of words. My pipeline consists in TF-IDF, followed by a <...
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0answers
21 views

Performing clustering without a distance matrix

I have n vectors and a matrix of similarity scores between them (e.g. vector 1 score of similarity with vector 4 is 1.3, and with vector 7 is 2.3). This matrix is ...
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2answers
38 views

Evaluation of Clustering method

I'm currently confused on choosing the method for evaluating different clustering techniques. From this paper, they followed the pipeline: use Hungarian assignment for matching the cluster with true ...
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1answer
12 views

Consistency between EM clusterings with varying starting point

I have a data set (~9 dimensions) in Weka and am running the EM clusterer with a fixed number of clusters. When changing the seed/initial point, the clusterings are very different. Is this expected? ...
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2answers
15 views

clustering,affinity propagation algorithm, minimal number of elements in one cluster

please could someone clarify the following: I apply Affinity Propagation (AP) algorithm to data set. The minimal number of elements in one cluster I got is three. In advance I know that my data set ...