Description Usage Arguments Details Value
The result has the following structure: - 1st dimension corresponds to the nth best match. - 2nd dimension corresponds to the number of queries. - 3rd dimension corresponds to the number of time series.
1 | FindBestNOccurrences(query, tss, n)
|
query |
KHIVA Array whose first dimension is the length of the query time series and the second dimension is the number of queries. |
tss |
KHIVA Array whose first dimension is the length of the time series and the second dimension is the number of time series. |
n |
Number of matches to return. |
For example, the distance in the position (1, 2, 3) corresponds to the second best distance of the third query in the fourth time series. The index in the position (1, 2, 3) is the is the index of the subsequence which leads to the second best distance of the third query in the fourth time series.
Array or KHIVA Arrays with the distances and indexes.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.