0
votes
0answers
19 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
52 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
26 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
112 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
17 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
47 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
0answers
11 views

R skmeans package - where does this error come from: “missing value where TRUE/FALSE needed” [migrated]

I tried to cluster my data in accordance with the manual provided by the skmeans packages's manual page I started by installing all required packages. I then imported my data table, and made a matrix ...
0
votes
1answer
25 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
37 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
146 views

Clustering a noisy data or with outliers

I have a noisy data of two variables like this. ...
-1
votes
1answer
27 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
84 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: ...
1
vote
2answers
91 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
58 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
47 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
38 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
62 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
32 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
71 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
108 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
46 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
52 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
32 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
40 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
46 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
34 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
0answers
27 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
46 views

Different hierarchical clustering results

I'm running a hierarchical clustering on a sample of data using the steps below: ...
0
votes
0answers
61 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
85 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
145 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
173 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
33 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
68 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
103 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
73 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
100 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
61 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
36 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
129 views
4
votes
2answers
150 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 ...
0
votes
3answers
75 views

Problem with PCA

I am trying to do some PC analysis on my data coming from lipids measurements in different samples. I only have one factor: if samples are diabetic or non-dibetic. Here is the PCA graph I get: As ...
-1
votes
1answer
57 views

Cluster with distance threshold in R

I'd like to get clusters with a maximum inner distance threshold. Now I use hc <- hclust(d) and cutree(hc, numofclasses). ...
1
vote
1answer
89 views

cluster plot: working and interpretation ?

Recently I have come across usage of cluster plot, which combines k-mean clustering along with PCA. The plot shows different clusters plotted using first two PCs. I have checked some of the threads ...
1
vote
0answers
66 views

Clustering time series of measurements in R

I have a dataframe consisting time series of measurements taken every hour for 366 days or a year. Below is shown a sample of hourly measurements for the first two weeks. I want to cluster days with ...
1
vote
0answers
48 views

Finding multivariate clusters with survey data (in R)

I'd like to conduct a multivariate cluster analysis on data from the American Community Survey's PUMS microsample (individual level records). I've only performed cluster analysis before when there are ...
1
vote
0answers
25 views

Clustering Techniques

I'm a little new to data mining and would definitely appreciate some tips. I'm using clustering algorithms looking for possible grouping in some variables described below. I've been using the Excel ...
2
votes
2answers
169 views

Special method for forecasting on time-series clusters in R?

I'm doing a project related to identifying sales dynamics. My database contains 26 weeks after launching the product (so 26 time-series observations equally spaced in time). I used two methods ...
1
vote
0answers
45 views

Advice on how to analyse “customer-data” in R

consider the following example data: ...