Database Reference
In-Depth Information
sequences and the reasons are:
1. Taking under consideration that a large portion of the sequences may
be just outliers, we need a similarity function that will be robust under
noisy conditions and will not match the incorrect parts. This property
of the
LCSS
is depicted in the Figure 7. Time Warping by matching all
elements is also going to try and match the outliers which, most likely,
is going to distort the real distance between the examined sequences.
In Figure 8 we can see an example of a hierarchical clustering pro-
duced by the
DTW
and the
LCSS
distances between four time-series.
Fig. 7.
Using the
LCSS
we only match the similar portions, avoiding the outliers.
Fig. 8. Hierarchical clustering of time series with significant amount of outliers.
Left:
The presence of many outliers in the beginning and the end of the sequences leads
to incorrect clustering.
DTW
is not robust under noisy conditions.
Right:
The
LCSS
focusing on the common parts achieves the correct clustering.
