TODO:

* The probability of each observation being used by the model is not 
  equal because of the sampling scheme. The observations towards the start
  and end of the time series are less likely to appear in the segments
  A fair sampling strategy is needed for segment selection.
  
* Currently the package requires UCR time series database format (each time 
  series is a row and columns are the observations over time). Therefore,
  time series are assumed to be the same length although LPS can handle
  time series of different length which requries changes in input format.
  
* LPS can work for multivariate time series similarity. Current version
  needs modifications for multivariate time series.
  
* LPS can work for categorical time series (i.e. DNA sequences). Current version
  requires modification for categorical variables
  
* Maximum depth parameter specifies the limit on the number of terminal
  (leaf) nodes. Hence, the depth of the trained trees can be larger based 
  on data characteristics. If tree is not balanced, trees with depth larger
  than maximum depth are expected to be built. On the other hand, similarity
  computations take the maximum depth into consideration. In other words, 
  some part of the tree might be useless (loss of time).
========================================================================
Change in 1.0-0:

* No recent news
