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[ENH] Correlations: Enhancements and fixes #3660

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merged 4 commits into from
Mar 8, 2019

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@VesnaT VesnaT commented Mar 6, 2019

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Implements the last part of #3504.

Description of changes
  • Improve heuristic to return all possible attribute pairs in most promising order, i.e. returning pairs within clusters first, followed by pairs among clusters (starting with closest clusters)
  • Show Need at least two continuous features. and Need at least two instances. messages as warnings
  • Fix feature model to contain only attributes (exclude class)
Includes
  • Code changes
  • Tests
  • Documentation

@VesnaT VesnaT changed the title Correlations: Enhancements and fixes [ENH] Correlations: Enhancements and fixes Mar 6, 2019
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codecov bot commented Mar 6, 2019

Codecov Report

Merging #3660 into master will increase coverage by 0.01%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master    #3660      +/-   ##
==========================================
+ Coverage   84.33%   84.35%   +0.01%     
==========================================
  Files         370      370              
  Lines       67896    67940      +44     
==========================================
+ Hits        57263    57309      +46     
+ Misses      10633    10631       -2

VesnaT added 2 commits March 6, 2019 10:40
Generate all possible attribute pairs, starting with pairs within clusters,
followed by pairs among clusters.
@VesnaT VesnaT force-pushed the correlations_heuristic branch from 1b0a16d to 6c363cd Compare March 6, 2019 09:40
@@ -206,9 +218,11 @@ class Outputs:
correlation_type = Setting(0)

class Information(OWWidget.Information):
removed_cons_feat = Msg("Constant features have been removed.")

class Warning(OWWidget.Warning):
not_enough_vars = Msg("Need at least two continuous features.")
not_enough_inst = Msg("Need at least two instances.")
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Could we make these messages proper sentences?

@janezd janezd self-assigned this Mar 7, 2019
instances = None # type: Optional[List]
centroid = None # type: Optional[np.ndarray]


class KMeansCorrelationHeuristic:
"""
Heuristic to obtain the most promising attribute pairs, when there are to
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to -> too
(not important, skip if you don't make any other, substantial changes)

Orange/widgets/data/owcorrelations.py Show resolved Hide resolved
@janezd janezd merged commit 6bd86e2 into biolab:master Mar 8, 2019
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2 participants