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holgerteichgraeber / TimeSeriesClustering.jl

Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets.
MIT License
82 stars 23 forks source link

Link to main Julia site; add corrected link to JuliaOpt site #120

Closed alansill closed 5 years ago

alansill commented 5 years ago

Correct link to https://www.juliaopt.org (instead of .com) and move it to the optimization reference in the last paragraph of the README. Replace initial Julia link with link to https://www.julialang.org

codecov[bot] commented 5 years ago

Codecov Report

Merging #120 into master will not change coverage. The diff coverage is n/a.

Impacted file tree graph

@@           Coverage Diff           @@
##           master     #120   +/-   ##
=======================================
  Coverage   64.49%   64.49%           
=======================================
  Files           9        9           
  Lines         521      521           
=======================================
  Hits          336      336           
  Misses        185      185

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update af20b39...b32220b. Read the comment docs.

codecov[bot] commented 5 years ago

Codecov Report

Merging #120 into master will not change coverage. The diff coverage is n/a.

Impacted file tree graph

@@           Coverage Diff           @@
##           master     #120   +/-   ##
=======================================
  Coverage   64.49%   64.49%           
=======================================
  Files           9        9           
  Lines         521      521           
=======================================
  Hits          336      336           
  Misses        185      185

Continue to review full report at Codecov.

Legend - Click here to learn more Δ = absolute <relative> (impact), ø = not affected, ? = missing data Powered by Codecov. Last update af20b39...b32220b. Read the comment docs.