0
votes
0answers
12 views

Term to Describe Strongly Clustered Data

I have some data which are strongly gathered into more than one cluster. I am looking for a term to effectively describe this phenomenon: e.g., multi-clustered data, which however seems to me that we ...
2
votes
2answers
88 views

Comparison of close data sets

I'm studying around 100 sets of temperature ($N_{sample}=500$), which depends $4$ explicative variables such as power or speed. The dependency is always the same in each set, but sometimes the mean ...
0
votes
0answers
24 views

What is data augmented by the additive inverse?

I am reading Biclustering of expression data (Cheng and Church, 2000) The paper is about the Cheng and Church biclustering algorithm and its main metric, the mean squared residue (MSR). It is said ...
4
votes
1answer
83 views

What algorithm should I use to cluster a huge binary dataset into few categories?

I have a large (650K rows * 62 columns) matrix of binary data (0-1 entries only). The matrix is mostly sparse: about 8% is filled. I would like to cluster it into 5 groups - say named from 1 to 5. I ...
1
vote
1answer
329 views

What data structure to use for my cluster analysis or what cluster analysis to use for my data?

I have a large dataset of categorical variables. The data consists of shoppers who purchased two items during a single trip to a store. There are approximately 75,000 cases and 1,500 different ...
0
votes
0answers
31 views

Can I use the variance of a set of observation as heuristic to decide how many times repeat an experiment?

I am applying a clustering algorithm (K-means) to a huge set of high dimensional data points (SIFT descriptors). The algorithm is not deterministic and its results depend on the initialization of the ...
0
votes
2answers
87 views

Can I replenish my dataset with unlabeled data?

I have a database of time series data generated by giroscope sensor. A small part of the data is already labeled and used to fit the model. My strong assumption is that most of the samples left in ...
4
votes
2answers
1k views

How do I find similarities between two sets of data

I have a group of data with 12 different football players, and they are rated for 11 different skills (speed, skill, flair, etc). I am looking to pair up individuals based on similar footballers, and ...
3
votes
2answers
981 views

Datasets for clustering algorithms

I am asked to give a lecture on clustering algorithms for an audience that is not very technical. With that in mind, I wanted to do a simple exercise where I will ask the audience to identify groups ...
2
votes
3answers
411 views

How to cluster survey data?

I have designed a rather long (250 Qn) survey designed to uncover user clusters. The questions are such that the pattern of answering should elicit user clusters, but I am having trouble uncovering ...
5
votes
2answers
924 views

Algorithms for clustering documents by similar words and phrases

I'm working on a project where I'm trying to take a pair of documents and find and group (cluster) similar words and phrases between them. Which algorithm would solve this kind of a problem? I know ...
7
votes
3answers
201 views

Mining search logs to improve autocomplete suggestions?

I have logs from an autocomplete form, which I would like to leverage to increase the intelligence of the results it returns. I have a project that revolves around users selecting opera characters ...
2
votes
4answers
2k views

How to convert nominal dataset into numerical dataset?

For my work, im using the multilabel dataset from this webpage. Few dataset which are listed in the page (for, e.g bibtex) have nominal attributes, i.e attribute values are 0 and 1. My queries are ...
4
votes
6answers
1k views

Looking for 2D artificial data to demonstrate properties of clustering algorithms

I am looking for datasets of 2 dimensional datapoints (each datapoint is a vector of two values (x,y)) following different distributions and forms. Code to generate such data would also be helpful. I ...
8
votes
2answers
729 views

When do we combine dimensionality reduction with clustering?

I am trying to perform document-level clustering. I constructed the term-document frequency matrix and I am trying to cluster these high dimensional vectors using k-means. Instead of directly ...
2
votes
1answer
191 views

What is heavy hitter analysis?

I have some data on the number of times each of my machines turned off (due to an error) in a particular time period. There are about 6 different classes of machines being used to construct a total ...