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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Question: next step after regression analysis? how to tell if multiple variables all co-correlate?

I am new to regression analysis and I have found that my 'independent variable' or predictor correlates with several dependent variables (through multiple linear regression tests) in a way that ...
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29 views

Data reduction by maintaining data distribution

I have n vectors with m features and also a weight vector with n elements. I'd like to reduce the number of n vectors in a way that the probability distributions of the m (weighted) features (across ...
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Situation that not well represented by hierarchical clustering

The below text is from statistical learning page 394. I highlighted where i stuck. Please help me to understand this. The term hierarchical refers to the fact that clusters obtained by cutting ...
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17 views

Cluster analysis considering uncertainty

Does anyone know how to do cluster analysis that considers the uncertainty (s.e. or confidence intervals in the data?) I want to do cluster analysis on group estimates state-level and regional ...
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29 views

Optics\dbscan produces cluster size smaller than minPts

I'm using optics from dbscan package: ...
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Help in understanding a clustering technique using neural network

I am having difficulty in understanding a technique for clustering and segmentation of biomedical images using the concept of time series. The paper on which the Question is based is : M. Lacomi et. ...
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1answer
59 views

Why not terminating the k-means clustering algorithm after one iteration?

Does anybody know whether there are applications of the k-means algorithm with only one iteration? (Of course, you may feel inclined to not call it k-means anymore in that case.) There is a clear ...
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Feature extraction from data in the form of many manifolds, in hierarchial structure and various dimensions

Is there a known feature extraction method which was developed to cope with data that satisfies the following assumptions?: The data points are real valued vectors in ...
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1answer
19 views

Grouping data in a multiline chart mean + outliers

I have an existing multi-line graph that displays time series data about success percentages of nodes in a cluster in 5 minute intervals, there are more than 50 nodes in the cluster and the way this ...
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1answer
24 views

spectra clustering vs hierarchical clustering

Can anyone please explain that is there any advantage of using hierarchical clustering over spectral clustering? I know how they work but I want to know in which situations its better to use ...
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1answer
16 views

How to map data to another feature space

I have some data which is described in a feature space $F$. Let's call this dataset $X_F$. That is, $X_F$ is a matrix where each row an instance and each column is a feature (characteristic). Suppose ...
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20 views

Evaluating kmeans clustering with silhouette coefficient, weird results

I'm performing a kmeans clustering on a 22.000 documents datasets. Not knowing how many clusters I should get, I ran different k values and try to assess the validity of the clusters by determining ...
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1answer
45 views

Optimal number of clusters for variables clustering

First of all, I know that this question has been addressed a certain number of times, but I didn't find an answer concerning the clustering of variables, instead of observations. Concretely, I am ...
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1answer
33 views

Calculating the adjusted rand index?

I'm really close to understanding the adjusted rand index, but I lack a background in formal maths and I'm struggling to grasp one or two things. I've been using the Wikipedia page primarily. I've ...
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16 views

Calculating internal clustering statistics (Distance Metric)

I have a quick question, which is probably more obvious than I am making it. When calculating internal cluster validation statistics (dunn coefficient, silhouette width), should I always be using ...
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Classifying empirical distributions without ground-truth

I have a big dataset of per-country viewing distributions that I want to cluster. The dataset contains 600,000 elements (I subsample it between 10 and 50 times to prevent swapping), and 242 countries ...
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6 views

Using Decision Rules to Make Cluster efect

I have a data set with 3 independent variables and 1 dependent variable. Dependent is play_golf Independents are Humidity, Pending_Chores, Wind I want to create "clusters" of rules and aggregate ...
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53 views

Cluster validation method for no cluster labels and differently sized clusters

I'm primarily a programmer and have little to no training in formal maths or statistics of any kind. I'm working on my dissertation (which foolishly is about clustering data), the process is ...
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60 views

Procedure of clustering seasonality in several time series in R

I want to do cluster analysis of a product monthly sales during 5 years in 30 stores (my data are time series). I want to cluster the stores according to its seasonality. This is an example of my ...
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31 views

Can I use the Xie-Beni index to validate data transformation parameters in fuzzy c-means clustering?

I am using fuzzy c-means algorithm to cluster my data in various feature spaces and the results differ depending on what kind of transformation I perform on my raw data. I want to know if using the ...
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A question about isoparametric clustering

I am reading this paper by Leo Grady and Eric L. Schwartz on Isoparametric Graph Partitioning: http://cns.bu.edu/~lgrady/grady2006isoperimetric_full.pdf On page 7, directly after equation (15), the ...
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41 views

Unsupervised clustering based on discriminant line

I have quite specific statistical problem, highly limited by its ecological interpretation. I have plenty of "time series" data - I need to link supression of photosythesis to the lack of light (PAR) ...
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2answers
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Regression with variable containing multiple entries per observation - clustering right approach?

Setting and Data I would like to run a 2-stage Hurdle regression with various variables describing the funding activity of companies (number of rounds, amount, etc). Some information on the data set: ...
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How to approach analyzing a dataset of baby speech?

I've been collecting speech data for my baby brother (who is now 6 months old) with the intention of doing computational analysis of the development of his speech patterns. I haven't much deep ...
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23 views

K-means with learning proces

I have a data set in which I already know the cluster to which each individual belong just by empirical observation but I want to predict, given the characteristics of a new individual in which ...
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1answer
46 views

Log likelihood in EM Algorithm

I try understand the log likelihood in weka. I read about that is a probabilistic metric, but i cant understand, if is better when have low value or high value? How i can get the likelihood value, ...
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3answers
59 views

Deterministic clustering approaches

I need a deterministic clustering method to group values in distributions that could be either random, normal or log-normal. Google mostly turns up k-means, which isn't deterministic. Fixing the ...
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1answer
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Segmentation of Geodemographic Data

I have a dataset that has 5 variables (columns). These are median house price, median income, number of people with no educational degree, number of people with high school degree, number of people ...
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75 views

Market Basket Analysis using Clustering to discover *new* product combinations

I have transaction data from a Quick Service Restaurant (QSR) client. Each record in this data set represents a transaction. My objective is to discover products that are the best candidates to be ...
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Comparing performance of kNN and kMeans

How do they compare performance wise in speed, accuracy, sparse, dense dataset ? Is it possible to somehow theorize what the runtime for kNN or means would be?
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1answer
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Using browser version types/numbers in Analysis in R

I am doing some analysis using survey data. The target variable is a customer satisfaction metric. It would be helpful to find what versions of what browsers, are causing low customer satisfaction so ...
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1answer
70 views

Standardization before PCA with data in same units and similar interval? [duplicate]

We have 16 variables which are indices produced by calculations based on ratio (unitless in fact). Some examples of the ranges of our variables are (0.450-0.750), (0.000 - 0.800) and (0.000 - 1.000). ...
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Spectral clustering or hierarchical clustering for this senario?

I have a data set of about 40,000 time series. The length of each time series is 64. I consider these 64 as features for the data. I want to cluster data into groups which have similar time series (I ...
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34 views

K - means clustering - visualize for multiple class

I clustered seperate dataset containing data from different classes. I want visualize all the clusters in one plot to see how much they overlap or if they even do overlap.
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1answer
24 views

Classifying unlabeled data, but with cost function

I need to classify objects with ~50 features into 3-4 different classes, there are no labeled examples. Moreover there is no absolutely correct class for any object. However I do have cost value for ...
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29 views

How to perform cross validation clustered input data?

How do i perform knn cross validation with input data that has been clustered using k-means. I seem to be unable to find the correct function which is able to do so. ...
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50 views

How to combine Euclidean and Cosine distance?

EDIT (No duplicate of Converting similarity matrix to (euclidean) distance matrix): This question is centered on asking how to combine values from Euclidean and Cosine distances obtained from ...
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Label reduction on dataset

This question related to this other one, for which I have devised a strategy and now want some feedback on it. My data consists of 434042 rows, each corresponding to an observation tagged with 1 of ...
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1answer
95 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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1answer
34 views

Model-based clustering evaluation with BIC

Let's say I have fitted two models using EM-clustering and they differ in both the number of clusters and are fitted on different subset of features (chosen from the same set of features). Could I ...
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51 views

2 Different F1-Measure to calculate clustering performance - which one is correct and why?

I know it sounds incorrect but that is the truth Here let me show you This below one is the first one and very widely used in the literature First one reference : Steinbach, Michael, George ...
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1answer
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Does Newman clustering work on weighted graph with non-integer weights?

I have a weighted undirected graph, where weight is distance and it is between 0 and 1. I want to apply the weighted version of Newman clustering. I think weight must refer to strength or similarity, ...
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10 views

How to predict new data goes which cluser in R [duplicate]

I already have k means output and i have segmented my users accordingly. Now, I have to predict cluster number for new users whenever they come. Do I have to run kmeans each time a new user comes into ...
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1answer
23 views

Fourier transform clustering

Which clustering algorithm would you use, moreover which distance measure, in case of analysis in frequency domain? I would like to perform Discrete Fourier Transform on time series and perform ...
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1answer
18 views

How to build a distance function given a cluster of points?

Given a non-elliptical cluster of points in a n-dimensional space I would like to get a distance function from the centroid of this cluster such that its "equipotential" surfaces has the same shape as ...
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Clustering methods ⊂ Unsupervised learning

Is it proper to say that clustering methods are mostly unsupervised learning techniques, with some exceptions such as model-based clustering?
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60 views

Stata: How to plot groups of variables side-by-side in stacked percent bar chart with subgraphs? [closed]

I did a cluster analysis of categorical variables and want to plot the result in a summary graph. There are three groups of variables that contain 'dummy variables'. I'm able to plot one group of ...
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21 views

Data to use for cluster analysis

I have a data frame of employees hours at work. The variables are time coming to work, time going home (finishing work), and time worked for the day, which is not the difference of going home and ...
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Rearrange 2D grid [closed]

I have a 2D grid on which I represent data points: Here, the red data point activates the grid on positions (1,1), (1,4) and (2,3). The blue data point activates the grid on positions (1,1), (4,3), ...
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15 views

Categorical Clustering of Users Reading Habits

I have a data set with a set of users and a history of documents they have read, all the documents have metadata attributes (think topic, country, author) associated with them. I want to cluster the ...