Skip to main content
Search type Search syntax
Tags [tag]
Exact "words here"
Author user:1234
user:me (yours)
Score score:3 (3+)
score:0 (none)
Answers answers:3 (3+)
answers:0 (none)
isaccepted:yes
hasaccepted:no
inquestion:1234
Views views:250
Code code:"if (foo != bar)"
Sections title:apples
body:"apples oranges"
URL url:"*.example.com"
Saves in:saves
Status closed:yes
duplicate:no
migrated:no
wiki:no
Types is:question
is:answer
Exclude -[tag]
-apples
For more details on advanced search visit our help page
Results tagged with
Search options not deleted user 106828

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.]

0 votes
0 answers
104 views

Cluster points generated by mixtures of linear functions

I have a data set of N points, n X variables plus Y variable. $$ (x^{(i)}_1,...,x^{(i)}_n,Y^{(i)}),\,\,\,\,i = 1,...,N $$ generated by a mixture of $k$ linear dependencies; with this, I mean that ther …
0 votes
2 answers
591 views

Reference for agglomerative clustering poor performance

Agglomerative clustering is known to have poor performance on mid-big size datasets in terms of memory and speed. …
6 votes
1 answer
8k views

Comparing a clustering algorithm partition to a "ground truth" one

If I feed a clustering algorithm with $X$, asking for $k$ clusters I would like to obtain a partition of the samples of $X$ that is the same of that induced by $y$, that is $P$. … I want to compare the partition generated by the clustering algorithm with the ground-truth partition $P$. …
2 votes
1 answer
4k views

K-means with high dimensional data [duplicate]

I read in many places that k-means clustering algorithm does not perform well when dealing with multidimensional binary data (so vectors whose entries are zero or one). …