Tagged Questions
1
vote
2answers
111 views
Why do we use k-means instead of other algorithms?
I researched about k-means and these are what I got: k-means is one of the simplest algorithm which uses unsupervised learning method to solve known clustering issues. It works really well with large ...
1
vote
0answers
29 views
Using PCA to merge and grade correlated items
I have a real estates' condos sold dataset with the following fields
DOM: Date on the market
sellPct: Percentage difference between the original and final price.
other fields such as Exposure( ...
0
votes
0answers
55 views
How to identify a new pattern in a URL with a machine learning algorithm (Text mining)
I am trying to identify new patterns after analyzing a number of URLs. So let's say, I am investigating the hypothetical website Yoohle.com and their URLs have the following structure.
domain = ...
8
votes
3answers
144 views
Detecting clusters in a binary sequence
I have a binary sequence such as 11111011011110101100000000000100101011011111101111100000000000011010100000010000000011101111
Where clusters of mostly 1's are ...
5
votes
1answer
120 views
Binary classification of DNA motif sequences (bioinformatics)
I've been working on on a method for binary classification of DNA
sequences. In more detail, here is what the method does.
Given a family of DNA sequences, for example DNA sequence
motifs, I try to ...
2
votes
0answers
38 views
Spectral Clustering of Graph
I am trying to cluster the graph using spectral clustering. However I am unaware of the number of classes that exist in the data.
Will it be a good idea to do PCA on the adjacency matrix to find ...
2
votes
2answers
281 views
Clustering high-dimensional sparse binary data
I am trying to cluster Facebook users based on their likes.
I have two problems: First, since there is no dislike in Facebook all I have is having likes (1) for some items but for the rest of the ...
2
votes
3answers
286 views
Which type of regression fits better?
I am a newbie in data mining world. I have a general question.
I have a data set which has 10 independent variables and one target variable named as category which has 9 values like: 1, 2, 3, 4, 5, 6, ...
0
votes
3answers
201 views
Clustering with 3 attributes
Please bear with me because I am very new to data mining.
I have a database of 3 attributes: latitude, longitude and temperature. I want to find clusters for the temperature data and I also want to ...
7
votes
5answers
238 views
Does preclustering help to build a better predictive model?
For the task of churn modelling I was considering:
Compute k clusters for the data
Build k models for each cluster individually.
The rationale for that is,that there is nothing to prove, that the ...
1
vote
1answer
255 views
Clustering of time series
I have a set of almost 1600 time series on 2 years which I want to group into clusters. Do you think this is possible using k-means? Which method do you advice me to use? Is this possible at all using ...
3
votes
2answers
132 views
Organizing cluster analysis results in a database
I'm a newbie in cluster analysis so please excuse me if my question seems to be very basic.
I'm using SPSS and Matlab for performing cluster analysis in a variety of datasets.
Dendograms are great for ...
2
votes
2answers
151 views
Finding most informative feature subsets given dataset, clustering algorithm and gold standard partition
I have an $n \times m$ matrix of data $\mathbf{D}$ as well as a $k$-partition $P$ of $n$ indices each representing a row in $\mathbf{D}$. Assuming an arbitrary clustering algorithm $A$, I would like ...
2
votes
1answer
461 views
2
votes
4answers
427 views
Clustering as a means of splitting up data for logistic regression
I'm trying to predict the success or failure of students based on some features with a logistic regression model. To improve the performance of the model, I've already thought about splitting up the ...
1
vote
3answers
313 views
Univariate clustering of time series
I just want to know if its possible to cluster an univariate time series, in order , say, to detect anomalies?
and do you have any online version for denstream code, in Matlab?
here is the time ...
14
votes
5answers
1k views
Euclidean distance is usually not good for sparse data?
I have seen somewhere that classical distances (like Euclidean distance) become weakly discriminant when we have multidimensional and sparse data. Why? Do you have an example of two sparse data ...
4
votes
5answers
3k views
Is cosine similarity a classification or a clustering technique?
In document classification, is cosine similarity considered a classification or a clustering technique? But you need training data with the cosine similarity for creation of the centroid right?
6
votes
1answer
179 views
How can I find out if a subset of Stack Exchange users increase/decrease their post rate based on badges earned?
I'm trying to mine that Stack Exchange data dump to find out whether there is a cluster of users that may be positively or negatively affected by the number of badges they've been awarded. The theory ...
2
votes
0answers
52 views
Regarding the size of training data for building classifier
When we build a classifier, like SVM or Naive Bayesian, are there any generic rules or theoretical derivations on the size of training data set? For example, to train a SVM-based classifier, what ...
7
votes
3answers
139 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 ...
5
votes
3answers
247 views
Books about incremental data clustering
Does anyone have a suggestion of any relatively recent and good book about data clustering?
More specifically, I'm looking for incremental clustering.
2
votes
1answer
164 views
What is the difference between frequent pattern mining, subspace clustering, and biclustering?
I have seen the terms "frequent pattern mining", "subspace clustering", and "biclustering". They all pertain to finding clusters using subsets of the data attributes. What's the difference?
4
votes
2answers
397 views
Will the silhouette formula change depending on the distance metric?
I am using Silhouette width to compute the best value for k in k-means. As I am performing document clustering, I am calculating the values of a and ...
0
votes
1answer
101 views
Notion of orthogonality in clustering
I'm reading in a paper "the goal is to cluster data in a way that is meaningful and at the same time as orthogonal as possible to the given classification"
Could someone have any idea how the notion ...
1
vote
3answers
336 views
Automating determination of number of clusters from a kmeans cluster analysis
I use kmeans for clustering a set of data. However, I have to specify the number of clusters. The problem is that sometimes I need 2 and other times I need 3 clusters.
Is there a clustering ...
3
votes
0answers
259 views
How to evaluate “external” quality of clustering?
Let's say you want to cluster some objects, say documents, or sentences, or images.
On the technical side, you first represent these object somehow so that you could calculate distance between them, ...
6
votes
1answer
318 views
Data mining approaches for analysis of sequential data with nominal attributes
Question for the experienced data miners out there:
Given this scenario:
There are N shopping carts
Each shopping cart is filled with an arbitrary number of M items from an infinitely large set ...
7
votes
2answers
518 views
Getting started with biclustering
I have been doing some casual internet research on biclusters. (I have read the Wiki article several times.) So far, it seems as if there are few definitions or standard terminology.
I was ...
