How to find unknown number of clusters in circular data? Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsEfficient dynamic clusteringExpectation number of points in initial clustering for LSHCan I apply Clustering algorithms to the result of Manifold Visualization Methods?Can clustering my data first help me learn better classifiers?t-SNE plotting DBSCAN clustering results very scattered issueHow to use cluster analysis with grouped data so one cluster may only have not more than one item from each group?Anomaly detection using clustering of highly correlated Categorical dataAnomaly detection in structured textual dataExtracting metrics from multiple classes of clustered objectsHow to validate clusters after calculating Gower distances and Ward's clustering in R
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How to find unknown number of clusters in circular data?
Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsEfficient dynamic clusteringExpectation number of points in initial clustering for LSHCan I apply Clustering algorithms to the result of Manifold Visualization Methods?Can clustering my data first help me learn better classifiers?t-SNE plotting DBSCAN clustering results very scattered issueHow to use cluster analysis with grouped data so one cluster may only have not more than one item from each group?Anomaly detection using clustering of highly correlated Categorical dataAnomaly detection in structured textual dataExtracting metrics from multiple classes of clustered objectsHow to validate clusters after calculating Gower distances and Ward's clustering in R
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I have some 1 dimensional data. Each record in the data is a specific time of the day. In order to cluster it I projected the data onto a circle of radius 1 unit. Now I need to find clusters in this data. The number of clusters are unknown and it is preferred to find clusters with high density of records in them. By density I mean that a large volume of records should be packed in a small space.
How should I go about finding clusters in the above mentioned data?
clustering unsupervised-learning
asked Jun 16 '18 at 11:35
SidSid
1011
$endgroup$
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I have some 1 dimensional data. Each record in the data is a specific time of the day. In order to cluster it I projected the data onto a circle of radius 1 unit. Now I need to find clusters in this data. The number of clusters are unknown and it is preferred to find clusters with high density of records in them. By density I mean that a large volume of records should be packed in a small space.
How should I go about finding clusters in the above mentioned data?
clustering unsupervised-learning
asked Jun 16 '18 at 11:35
SidSid
1011
$endgroup$
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I have some 1 dimensional data. Each record in the data is a specific time of the day. In order to cluster it I projected the data onto a circle of radius 1 unit. Now I need to find clusters in this data. The number of clusters are unknown and it is preferred to find clusters with high density of records in them. By density I mean that a large volume of records should be packed in a small space.
How should I go about finding clusters in the above mentioned data?
clustering unsupervised-learning
asked Jun 16 '18 at 11:35
SidSid
1011
$endgroup$
I have some 1 dimensional data. Each record in the data is a specific time of the day. In order to cluster it I projected the data onto a circle of radius 1 unit. Now I need to find clusters in this data. The number of clusters are unknown and it is preferred to find clusters with high density of records in them. By density I mean that a large volume of records should be packed in a small space.
How should I go about finding clusters in the above mentioned data?
clustering unsupervised-learning
clustering unsupervised-learning
asked Jun 16 '18 at 11:35
SidSid
1011
asked Jun 16 '18 at 11:35
SidSid
1011
asked Jun 16 '18 at 11:35
SidSid
1011
asked Jun 16 '18 at 11:35
SidSid
1011
asked Jun 16 '18 at 11:35
SidSid
1011
1011
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 28 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
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$begingroup$
Instead of projecting into the circle and thus making your problem 2d, why don't you just use a cyclic distance measure?
This problem should be straightforward by doing kernel density estimation on the (cyclic) time of day. Then find the peaks, which are your clusters.
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
$endgroup$
add a comment |
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$begingroup$
Instead of projecting into the circle and thus making your problem 2d, why don't you just use a cyclic distance measure?
This problem should be straightforward by doing kernel density estimation on the (cyclic) time of day. Then find the peaks, which are your clusters.
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
$endgroup$
add a comment |
$begingroup$
Instead of projecting into the circle and thus making your problem 2d, why don't you just use a cyclic distance measure?
This problem should be straightforward by doing kernel density estimation on the (cyclic) time of day. Then find the peaks, which are your clusters.
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
$endgroup$
add a comment |
$begingroup$
Instead of projecting into the circle and thus making your problem 2d, why don't you just use a cyclic distance measure?
This problem should be straightforward by doing kernel density estimation on the (cyclic) time of day. Then find the peaks, which are your clusters.
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
$endgroup$
Instead of projecting into the circle and thus making your problem 2d, why don't you just use a cyclic distance measure?
This problem should be straightforward by doing kernel density estimation on the (cyclic) time of day. Then find the peaks, which are your clusters.
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
answered Jun 19 '18 at 7:06
Anony-MousseAnony-Mousse
5,195625
5,195625
add a comment |
add a comment |
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