All Questions
7 questions with no upvoted or accepted answers
2
votes
0
answers
94
views
What are the simple methods to do an unsupervised cluster to stock return time series?
I am a student in finance and I am working on my thesis project. I am interested in doing a clustering to stock time series. I first read the paper 'Time-series clustering – A decade review' from ...
2
votes
0
answers
85
views
Univariate clustering for longitudinal cohort
We have screening information on thousands of patients followed for several years. We also have their cancer outcomes, whether or not such cancers were identified by screening or were otherwise ...
1
vote
0
answers
457
views
Best practice/Ideas for clustering Event Sequence Embeddings?
My dataset consist of around 40 000 samples of event sequences.
Sample of data
[[Event 1, Event 2, Event 4, Event 5],
[Event 1, Event 3, Event 4],
[...]]
I ...
1
vote
0
answers
306
views
How to achieve good clustering results in subsequence time series clustering with DBSCAN?
I want to find patterns in a time series and use clustering for that. Before I cluster, I create subsequences from the time series using a sliding window approach. (STS-clustering)
So far I have tried ...
1
vote
0
answers
708
views
Joint probability distribution function between different time-series clusters
I have 24-hour time-series data-sets for Solar Power and Power Consumption respectively for an entire year i.e 365x24 data set. Intuitively, the data set captures the variation of each of the ...
0
votes
0
answers
89
views
Silhouette Score for ordered clusters
My clusters are arranged according to a time series, and I want to compute the silhouette score for the clustering performed, considering that they follow an order. Therefore the nearest cluster to ...
0
votes
1
answer
192
views
clustering location based on sorted time
I clustered my dataset based on location using DBSCAN(haversine). Everything is OK until this. However, I'd like to use the time series while I'm clustering my dataset. For example. You were at home ...