0
votes
0answers
8 views

R Clustering Evaluation (Adaptive Kmeans)

i know there are several threads about this topic, but most i read, most i get confused. I'm doing a project that consists in clustering some data (news articles). I used adaptive Kmeans ...
1
vote
0answers
20 views

How can you cluster a set of functions with unknown functional forms?

Say you've $N$ functions $f_N(x)$ defined on a regular grid $x$. You don't know the form of $f(x)$, you've only got several realizations of it. The different functions are related to each other ...
0
votes
0answers
28 views

find group of rows in a matrix with pattern similar to another matrix

I've been scratching my head about this problem for some time: I have a big gene expression dataset (20k genes x 200 samples) in matrix A and i have a subset of this dataset (i.e. 40 genes x 200 ...
0
votes
0answers
26 views

How to do clustering using genetic algorithm?

I am studying how to use genetic algorithm (GA) in clustering analysis on R programming. What I understand now is that we have to determine fitness function in GA. That is, we have to minimize within ...
0
votes
0answers
38 views

Variable Clustering Analysis

I have a data set that consists of 143 variables (~11000 observations), and I wish to do variable clustering to reduce the dimension. I am using hclustvar function ...
0
votes
1answer
31 views

Autoclass in R/Python? [closed]

Are there any packages that implement the Autoclass/ Naive Bayes Clustering algorithm in R or Python? Alternatively, what are some other clustering algorithms that can handle both categorical and ...
0
votes
0answers
20 views

Interpreting R results, are the data multivariate normal?

I ran "mvn" using the "mclust" package in R using the following codes: mvn("EEE", data[,18:22], prior = NULL, warn= NULL) I am having trouble figuring out how to ...
0
votes
1answer
43 views

Comparing mclust() and k-means centroids

I have some code that looks for clusters in x,y data. To check the number of clusters I use, I want to get the BIC. This is not possible (easily) using kmeans(), ...
0
votes
0answers
50 views

why Hierarchical Clustering pvclust vs. hclust got different result?

I am performing the hierarchical clustering analysis on a dataset of 25 viral populations using 3 viral components (variables) to construct a dendrogram with average method and correlation distance ...
0
votes
0answers
24 views

breakpoint analyses on multiple series: how to detect common points

I have 20 time series that span the same period (100 days each), from 4 species sampled at 5 different location. I made a loop to perform a breakpoint analysis on all of them, resulting in 0 to 3 ...
0
votes
1answer
58 views

How to determine which variable or combination of the variables are affecting to the predictor variable?

I have one dependent variable name as "win ration" of the deal contested and more than 30 independent variables, all are categorical variable name as role of the customer, geo, region, and 27 ...
0
votes
1answer
34 views

NbClust package r error

I try to do: NbClust(city, diss =d, distance = NULL, min.nc = 2, max.nc =5,method = "kmeans", index = "all", alphaBeale = 0.1) with city is a list of number ...
4
votes
1answer
114 views

how to discard values that are far from center of cluster in mixture model

I am trying to fit a bivariate cluster model with X and Y. What I would like to do is discard (make not clustered / un-grouped) that are far from the cluster center (for example $\mu$ + 2*standard ...
0
votes
0answers
21 views

Hierarchical clustering of repeated measures in a few locations

I have a water quality data (value) measured 10 times (every month - data) on three depths (shallow, medium, deep) in five location (A, B, C, D, E): I want to find in which location values are ...
2
votes
2answers
52 views

How to fit mixture model for clustering

I have two variables - X and Y and I need to make cluster maximum (and optimal) = 5. Let's ideal plot of variables is like following: I would like to make 5 clusters of this. Something like this: ...
0
votes
1answer
38 views

Spherical K-means Clustering in R

I have a large data set that I would like to cluster using spherical K means algorithm. However, I am relatively new to this subject and R in general. Most of my knowledge is self taught and I am ...
4
votes
1answer
39 views

how to complement the results of cluster analysis with known groups

I have some prior knowledge of grouping, but this may be incorrect or is not sufficient as I need larger number of groups (i.e. subgroups). For example in the following data I have 3 groups in ...
6
votes
2answers
160 views

Clustering a noisy data or with outliers

I have a noisy data of two variables like this. ...
-1
votes
1answer
30 views

Weighting related attributes in hierarchical clustering

I have two questions about output of hierarchical clustering and improving the output. I'm trying to learn more about performing hierarchical clustering in R so I started looking at a simple dataset ...
1
vote
1answer
86 views

calculating probability or filtering that certain subject is not in the particular cluster

I have a situation where there are n individuals and p features (variables). I do have their cluster information. Here is an example: ...
2
votes
2answers
157 views

What algorithm does ward.D in hclust() implement if it is not Ward's criteria?

The one used by option "ward.D" (equivalent to the only Ward option "ward" in R versions <= 3.0.3) does not implement Ward's (1963) clustering criterion, whereas option "ward.D2" implements ...
1
vote
2answers
65 views

K means clustering inadequate in determining extreme regions in R

I want to identify the regions that are considerably higher than the highest cluster. (The obvious regions which should be identified as their own clusters, notably at the x coordinate ~10 e+07. How ...
0
votes
1answer
48 views

identify different points [closed]

I have a large scatterplot, with about 100,000 (x,y) points. The x coordinate is the set of numbers from (1 to ~100,000) - in other words, no 2 points have the same x-coordinate. The y is mostly ...
1
vote
1answer
52 views

How to choose the right distance matrix for clustering?

I am attempting simple Ward type clustering. However, the R package is proving several choices to use for the distance matrix. I am wondering how I am supposed to determine the right distance matrix ...
0
votes
1answer
84 views

Clustering high dimensional data (p > n) in R

I have a situation where we have a number of quantitative features / variables (p) than the number of samples (n). My objective is to classify these samples into groups (may be hierarchical). I can ...
1
vote
1answer
36 views

Creating a cluster analysis on multiple variables

I am working on creating a cluster analysis for some very basic data in r for Windows [Version 6.1.76]. The groups themselves are countries and then I have 2 column with continuous numerical ...
0
votes
1answer
105 views

hclust, R and Euclidean distances: weird stuff

I have a table of similarities expressed through cosines and am trying to do some cluster analysis in R, using hclust and ...
1
vote
1answer
124 views

Pull out most important variables from PCA

I would like to get the most important variables from a PCA result. I see two clusters in the plot. I now that is possible that there is no only one variable causing this, so maybe I would have to get ...
0
votes
1answer
55 views

using cluster information in multiple imputation

i need to impute a dataset all categorical variables before doing analysis. I can just simply impute with mode of all data or a variable. I belief that better option will be to classify the subjects ...
0
votes
0answers
62 views

(Spatial) distance between cluster means

I'd like to cluster points based on a distance criteria. As I want to cluster spatial points I am using euclidean distance and a hierachical cluster approach. In a final step I'd like to cut the ...
0
votes
0answers
41 views

Spectral clustering using RBF Kernel function in R

I have extracted user-features and item features in my recommender system using a modified SVD approach built on ALSE (loosely based on Yehuda Koren's paper). I now want to cluster items not directly ...
0
votes
0answers
56 views

Performance of hierarchical clustering for binary data in R

I am trying to use Hierarchical clustering to see how well it performs in classifying a dataset which I previously know its true classification. I am new to clustering in general. I was able to draw ...
1
vote
0answers
90 views

Cophenetic distance matrix to a dendrogram

In hierarchical clustering procedure, a distance matrix is used to construct a dendrogram with an appropriate method of clustering. In the process of constructing a dendrogram, a cophenetic matrix is ...
1
vote
1answer
47 views

Extract (ultrametric) distances from hclust or dendrogram

How can the matrix of (ultrametric) distances be extracted from the result of hclust (or a dendrogram in general) in R? The ...
0
votes
1answer
42 views

Implementation for Co-Clustering

I am looking for existing implementations for co-clustering (aka biclustering). I came up with biclust function available in MATLAB, but still I am wondering if ...
1
vote
1answer
55 views

Different hierarchical clustering results

I'm running a hierarchical clustering on a sample of data using the steps below: ...
0
votes
0answers
78 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...
2
votes
1answer
133 views

Is there a decision-tree-like algorithm for unsupervised clustering?

I have a dataset consists of 5 features : A, B, C, D, E. They are all numeric values. Instead of doing a density-based clustering, what I want to do is to cluster the data in a decision-tree-like ...
0
votes
1answer
193 views

Outlier detection using clustering and dissimilarity matrix in R

I have some problems in finding the outliers using clustering. The data.frame is ~20000 observations and each row has mixed types of variables(numeric, nominal and binary). What I want to do is to ...
3
votes
1answer
210 views

Using PC scores or cluster analsis in predictions

I have very big data and low number of observations. So I decided to use PCA to reduce dimension of the data. The following is R example (just an dummy example - for workout): ...
1
vote
1answer
37 views

Similarity between different length vectors containing related items

I have a vector (V1) with which I need to calculate the similarity of other vectors (ex V2,V3 ... ) which may be of different lengths. The different angle here is that the elements inside the vectors ...
1
vote
1answer
79 views

Approximating a Complementary Cumulative Distribution Function via a piece-wise function

I hope this is not too much to read, but I tried to give you a specific overview over my problem. I am currently trying to model the German electricity market, with a special focus on balancing ...
2
votes
2answers
122 views

How can I cluster data in a grid-like fashion and heat map the averages in R?

I have a data frame of 3 columns. The first one is the response variable the second and the third ones are some criteria. You can create your own example similar to mine, using this piece of code with ...
2
votes
1answer
76 views

Is there a package that I can use in order to get rules for a target outcome in R

For example In this given data set I would like to get the best values of each variable that will yield a pre-set value of "percentage" : for example I need that the value of "percentage" will be ...
4
votes
1answer
129 views

Clustering data that has mixture of continuous and categorical variabes

I have data that represent some aspect of human behavior. I want to cluster it (unsupervised) into behavioral profiles of some sort. now, some of my variables are categorical (with 2 or more ...
0
votes
1answer
81 views

Interpretation of NbClust result

The plots show the output of NbClust(). By looking at the plot, is that correct to say that k=5 is the optimal number of ...
0
votes
1answer
41 views

Cluster analysis

I am trying to cluster cells (1×1km) over a specific area. Each cell is composed of various habitats defined by a code. (Each habitat consists of 3 parameters, so a habitat code looks like e.g. ...
2
votes
1answer
226 views
4
votes
2answers
200 views

Is there an advantage to squaring dissimilarities when using Ward clustering?

Is there a reason to prefer squaring or not squaring the dissimilarities when clustering with Ward's method? The question is motivated by the following statement in the documentation for R's ...
0
votes
1answer
24 views

Algorithms that use multiscaler properties of data to cluster

I was thinking of devising a clustering algorithm (for fun and kicks) that would cluster data by looking at the distribution of the data at multiple scales. For example say my data was distributed on ...