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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Bag of Visual Words: the number of words is equal to the number of k-means centroids?

I was reading these slides about Bag of Features (BoF), in particular at slide 23: A visual vocabulary of 1M words is generated using an approximate K-means clustering method based on randomized ...
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1answer
16 views

Mix of n normals with known locations

I have data points that are generated with the $n$ normal distributions with the same $\sigma$ and different means. I do not know $n$, but I know that $1 \leq n \leq 4$. I know the possible set of ...
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1answer
126 views

Alternate distance metrics for two time series

I have time-series data of different houses. Assume it is power consumption data. Now, I want to cluster the houses following similar power consumption pattern utmost. So, the various distance metrics ...
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1answer
23 views

How to visualize separate categories that share common features with radar charts?

I am working on a scientific research project with a real data-sample where I have applied EM clustering algorithm based on 5 criteria (e.g. Var1, Var 2, Var3, Var4, Var5)and I finally got 5 clusters ...
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1answer
209 views

How to consider different samples in functional data clustering?

In the engineering context several data sources like different kinds of measurement signals (for example distances, angles and efficiencies) are very common. If it would be possible to observe these ...
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14 views

compare the similarity of two cluster results using igraph

i am comparing the results of two clusters using igraph, such as What is the intuition behind the variation of information (VI) metric for cluster validation? I see there were consistency for all ...
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1answer
143 views

K-Medoids swapping inside clusters

I'm a bit confused with concept of K-medoids. It seems that original algorithm (PAM) describes that swap step should be performed by swaping only one of the medoids with one non-medoid point from ...
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0answers
20 views

Best approach for this non-supervised clustering problem?

I'm a software engineer new to Machine Learning. I've read about basic non-supervised techniques like k-means and hierarchical clustering and now I'm trying to put them into practice with a basic ...
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1answer
24 views

Randomized groups for A/B testing

I have the dataset where the dimension = 10 and number of samples = 20. Let's denote the features by $x_1, x_2, ..., x_{10}$. I'd like to analyze the effect of $x_2$ on $x_1$. I applied the following ...
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1answer
16 views

How to implement density-based clustering?

I’m looking to implement density-based clustering with R or Mathematica on a giant file (600,000 points on a 3 billion x 3 billion plane). Is DBSCAN the right method for data that is this sparse? I am ...
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16 views

What are some of the existing methods (preferably with implementations) that cluster dynamic brain network data with signed edge weights?

I have a dynamic graph data with nodes and edges attributed to each timestep. The problem is to find how many communities are found at each timestep and what is their membership. I have an existing ...
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21 views

Bag of Features: why the distance between two histograms of the same image is different than 0?

I'm trying to implement a Content Based Image Retrieval application for small image datasets. I'm testing it just with 1 thousands images from Caltech1001. The approach that I'm using is the classic ...
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2answers
46 views

What does it mean an histogram vector normalization with L1/L2 norms?

I was reading these slides about Bag of Features (BoF). At slide 23 you can read: each image is represented by a vector, typically 1000-4000 dimension, normalization with L1/L2 norm What does ...
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0answers
15 views

clustering for mixed data [on hold]

i'm student in statistics ( i'm sorry for my poor english)and i want do a clustering for a data that contains a groups of qualitative and quantitative variable, but i want do this in R and without any ...
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1answer
14 views

Can we use Bag of Visual Words to compute similarity between images directly?

I'm implementing a Content Based Image Retrieval application (CBIR). I've read about the Bag of Features model and it's considered an intermediate-step algorithm in some application. For example, ...
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0answers
10 views

How to group/cluster variables/features using Python? [on hold]

I have 200 variables and 1 million records. I want 20 clusters, so that I can pick out top variable (based on Information Values of the variables) in each cluster.
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0answers
13 views

alignment of many curves for getting one curve [on hold]

I have a graph with for curves which look almost the same; I would like to align these curves in order to obtain only one curve with the variations of the four curves. Thanks a lot for helping me.
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3answers
172 views

Analysing data on importance ratings

I had following question in my questionnaire: Rate the following factors: price, quality, advertisement, brand, reference from 1 (very important) to 5 (least important) that may have influenced your ...
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3answers
410 views

How to select or validate the selection of a clustering method?

One of the biggest issue with cluster analysis is that we may happen to have to derive different conclusion when base on different clustering methods used (including different linkage methods in ...
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2answers
25 views

Comparing clustering algorithms [duplicate]

I am conducting clustering analysis in which I am using three clustering algorithms K-means, Spectral Clustering, and ...
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1answer
28 views

Class imbalance in clustering

Is there is a problem for clustering if the dataset is highly imbalanced? I have a clustering task and it looks like that there is a realy huge peak whose tail covers other clusters. Are there any ...
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0answers
8 views

calculate density in IDILCA algorithms [closed]

How to calculate the density and form density matrix in the algorithm DILCA or IDILCA (step 3) on matlab? Thank you. file: http://file.scirp.org/pdf/OJS_2015061015144079.pdf
140
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7answers
17k views

Why is Euclidean distance not a good metric in high dimensions?

I read that 'Euclidean distance is not a good distance in high dimensions'. I guess this statement has something to do with the curse of dimensionality, but what exactly? Besides, what is 'high ...
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2answers
29 views

Creating clusters for binary data

I have a set of data with patients and their diseases. I would like to use hierarchical clustering or some kind of cluster analysis to make a dendrogram to see which diseases cluster together in this ...
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2answers
175 views

How to generate new Topic for new documents?

what approach would help me generate new topics for new documents? I read this page in order to learn more about the effect of specifying keywords for the topics that we care about detecting in new ...
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1answer
206 views

R - How to fix NbClust error with error message: “The TSS matrix is indefinite. There must be too many missing values.”

I would like to know how I can use clustering methods in R (in this case, Kmeans) if I have an "unkind" input matrix (I get this error log: The TSS matrix is indefinite. There must be too many ...
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3answers
37 views

Is K-means performance a bottleneck everywhere?

I've read a paper about a sped-up version of k-means: Ding et al. (2015). Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup. Now I wonder, is k-means' ...
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2answers
155 views

Finding words belonging to a topic

Consider forum posts or any text where we'd be interested in finding out related words, given the data. What would be a solution for creating a topic cluster based on this data? E.g. We are interested ...
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Neural Chess, Neurons And Hidden layers! [closed]

Hi I am wanting to make a Gigantic Chess Neural Network, I was wanting to have 800 base Neurons that feed into the Hidden layers I also want to have 3 Hidden layers of 800 Neurons each at it's ...
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3answers
5k views

Clustering a long list of strings (words) into similarity groups

I have the following problem at hand: I have a very long list of words, possibly names, surnames, etc. I need to cluster this word list, such that similar words, for example words with similar edit (...
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0answers
8 views

shall I expect the same number of clusters in cluster analysis as the same number of classes from LCA?

Both cluster analysis and latent class analysis are aiming to group the cases into groups. If I do cluster analysis and latent class analysis using the same variables, shall I expect the same number ...
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1answer
23 views

cluster analysis after factor analysis: do I need to use all factors for cluster analysis?

I have a 127-question survey with 6-level likert type answers. With EFA I have kept 56 items and got 8 factors. With CFA (on sample not used in EFA) I confirmed these factors. so far all good. When I ...
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0answers
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can anyone help me to find out the working of Expectation Maximisation clustering [closed]

1)how clusters are build using EM clustering when given a set of data points as input. 2)how EM is different from k-means clustering. 3)give a detailed explanation of E-step and M-step of EM ...
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24 views

hierarchical cluster analysis in SPSS with ordinal data

I have ordinal data on scale 1-5 for detected pollutants in water (1 = detectable in small proportions; 5= detectable in higher proportions; also 0 was asaigned - not detectable). I want to do HCA ...
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0answers
50 views

Interpreting clusters on my heatmap

I have a dataset of binary variables similar to the dataset in this post. I created a heatmap by clustering on both rows and columns. The red cells correspond to zeros and yellow cells correspond to ...
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1answer
18 views

Predicting continuous position using input variables of unknown quality

The problem I'd like to solve can be reformulated as follows. Let's consider that I have to go to some parties and I would like to find out where in the room I am most likely to have a good time. I ...
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0answers
16 views

Silhouette score significance: what is a significant increase in silhouette score?

I'm aware a silhouette score ranges from -1 to 1. But what can be considered a significant increase? 0.1 to 0.2 (because 100%) or 0.5 to 0.6? Obviously higher is better, but is there some measure of ...
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1answer
2k views

SSB - Sum of squares between clusters

I got a little confused with the squares and the sums. As far as I know, the variance or total sum of squares (TSS) is smth like $\sum_{i}^{n} (x_i - \bar x)^2$ and the sum of squares within (SSW) ...
2
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0answers
20 views

Cluster analysis with PC scores (Multivariate Morphometrics)

I have a morphometric dataset of 430 fish, with 27 various "shape" measurements, for example: total length, head length, fin distances, etc. My goal is multi-fold: (BIG GOAL: cluster by "shape") ...
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0answers
14 views

Which clustering method and number of clusters?

during a cluster analysis procedure, how would I approach finding an appropriate number of clusters within my data? I've been experimenting with kmeans a little doing the following: run kmeans (with ...
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31 views

Are negative values acceptable for the Variance Ratio Criterion (VRC)?

I'm using a tutorial for the Variance Ratio Criterion (VRC) by Calinski and Harabasz 1974 (pdf). In my case this entails the following steps: Conduct k-means clustering on my dataset for k=2 to k=...
2
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3answers
34 views

Comparing silhouette scores between different datasets (having different number of variables)

Full Question Experiment 1 clustered data using variables X and Y. Experiment 2 clustered data using variables X, Y and Z (i.e. a third variable was added). Would it be valid to compare silhouette ...
2
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1answer
436 views

Unsupervised Clustering using randomForest

Outline of clustering technique using Random Forest A synthetic data is created by randomly sampling from the data of interest. It is used as the base line to measure the "structureness" or "...
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2answers
33 views

Any distance measures that are more useful for binary data clustering?

I was taking a look at Clustering a binary matrix but it didn't seem to answer my question. I used a basic euclidean distance measure which definitely works but I am exploring alternative distance ...
2
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1answer
22 views

Classification of samples into two groups

I'm having problems finding what is the right perspective on the following problem. I have a set of (univariate) samples: $$S_1 = \{X^1_1,\ldots ,X^1_{n_1}\},$$ $$S_2 = \{X^2_1,\ldots ,X^2_{n_2}\},$$...
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2answers
49 views

Clustering groups of observations

I am having a situation where my data points consist of $r$ groups, that we want to force the observations within a group to be in the same cluster, with $n_r$ observations in each group. So the idea ...
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3answers
37 views

How to group/cluster similar words

Let say I have a list of words, such as: apple apale aaple apples oranges ornnges orange orage melons meeons meeon melon melan I want to group them based on ...
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0answers
15 views

collapse a cross-validation matrix to a single value

I want to compare the sensitivity of a clustering solution to the inclusion of different subjects in the dataset using leave-one-out cross-validation. I use Variation of Information (VI) to compare ...
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3answers
51 views

Maximize response for input params clusters from a blackbox function

I have a blackbox function which takes finite number of integers V1, V2, Vn parameters and based on time series variable produce a scalar response. I would like to ...