From d33b9961d9ae0eb082de1371880b4d0b47f4f973 Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin.1@ulaval.ca>
Date: Tue, 21 Nov 2017 08:38:18 -0500
Subject: [PATCH] WE work
---
Code/MonoMultiViewClassifiers/Metrics/accuracy_score.py | 2 +-
Code/MonoMultiViewClassifiers/Metrics/f1_score.py | 4 ++--
Code/MonoMultiViewClassifiers/Metrics/fbeta_score.py | 4 ++--
Code/MonoMultiViewClassifiers/Metrics/hamming_loss.py | 2 +-
.../Metrics/jaccard_similarity_score.py | 2 +-
Code/MonoMultiViewClassifiers/Metrics/log_loss.py | 2 +-
.../MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py | 2 +-
Code/MonoMultiViewClassifiers/Metrics/precision_score.py | 4 ++--
Code/MonoMultiViewClassifiers/Metrics/recall_score.py | 4 ++--
Code/MonoMultiViewClassifiers/Metrics/roc_auc_score.py | 6 +++---
Code/MonoMultiViewClassifiers/Metrics/zero_one_loss.py | 2 +-
Code/MonoMultiViewClassifiers/ResultAnalysis.py | 8 +++-----
12 files changed, 20 insertions(+), 22 deletions(-)
diff --git a/Code/MonoMultiViewClassifiers/Metrics/accuracy_score.py b/Code/MonoMultiViewClassifiers/Metrics/accuracy_score.py
index a51d11b7..86762167 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/accuracy_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/accuracy_score.py
@@ -11,7 +11,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
"""Arguments:
y_true: real labels
y_pred predicted labels
diff --git a/Code/MonoMultiViewClassifiers/Metrics/f1_score.py b/Code/MonoMultiViewClassifiers/Metrics/f1_score.py
index 78e2d2ba..13633903 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/f1_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/f1_score.py
@@ -11,7 +11,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
@@ -27,7 +27,7 @@ def score(y_true, y_pred, **kwargs):
try:
average = kwargs["3"]
except:
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
average = "micro"
else:
average = "binary"
diff --git a/Code/MonoMultiViewClassifiers/Metrics/fbeta_score.py b/Code/MonoMultiViewClassifiers/Metrics/fbeta_score.py
index 6fc91278..aa2c9298 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/fbeta_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/fbeta_score.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
@@ -26,7 +26,7 @@ def score(y_true, y_pred, **kwargs):
try:
average = kwargs["4"]
except:
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
average = "micro"
else:
average = "binary"
diff --git a/Code/MonoMultiViewClassifiers/Metrics/hamming_loss.py b/Code/MonoMultiViewClassifiers/Metrics/hamming_loss.py
index 2ad6e26c..1adbc376 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/hamming_loss.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/hamming_loss.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
classes = kwargs["0"]
except:
diff --git a/Code/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py b/Code/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py
index fff71707..38500825 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/jaccard_similarity_score.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
diff --git a/Code/MonoMultiViewClassifiers/Metrics/log_loss.py b/Code/MonoMultiViewClassifiers/Metrics/log_loss.py
index 7a748037..4a771e42 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/log_loss.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/log_loss.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
diff --git a/Code/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py b/Code/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py
index 3f077474..5d69563f 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/matthews_corrcoef.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
score = metric(y_true, y_pred)
return score
diff --git a/Code/MonoMultiViewClassifiers/Metrics/precision_score.py b/Code/MonoMultiViewClassifiers/Metrics/precision_score.py
index 09d63e64..a8087841 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/precision_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/precision_score.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
@@ -22,7 +22,7 @@ def score(y_true, y_pred, **kwargs):
try:
average = kwargs["3"]
except:
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
average = "micro"
else:
average = "binary"
diff --git a/Code/MonoMultiViewClassifiers/Metrics/recall_score.py b/Code/MonoMultiViewClassifiers/Metrics/recall_score.py
index 194e1066..7ce329a9 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/recall_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/recall_score.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
@@ -22,7 +22,7 @@ def score(y_true, y_pred, **kwargs):
try:
average = kwargs["3"]
except:
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
average = "micro"
else:
average = "binary"
diff --git a/Code/MonoMultiViewClassifiers/Metrics/roc_auc_score.py b/Code/MonoMultiViewClassifiers/Metrics/roc_auc_score.py
index ed03c774..4f2cc4db 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/roc_auc_score.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/roc_auc_score.py
@@ -7,7 +7,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
@@ -15,11 +15,11 @@ def score(y_true, y_pred, **kwargs):
try:
average = kwargs["1"]
except:
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
average = "micro"
else:
average = None
- if set(y_true) != {0,1} or (set(y_pred) != {0,1} and set(y_pred) != {0} and set(y_pred) != {1}):
+ if multiclass:
mlb = MultiLabelBinarizer()
y_true = mlb.fit_transform([(label) for label in y_true])
y_pred = mlb.fit_transform([(label) for label in y_pred])
diff --git a/Code/MonoMultiViewClassifiers/Metrics/zero_one_loss.py b/Code/MonoMultiViewClassifiers/Metrics/zero_one_loss.py
index ea0b6478..cf632fed 100644
--- a/Code/MonoMultiViewClassifiers/Metrics/zero_one_loss.py
+++ b/Code/MonoMultiViewClassifiers/Metrics/zero_one_loss.py
@@ -6,7 +6,7 @@ __author__ = "Baptiste Bauvin"
__status__ = "Prototype" # Production, Development, Prototype
-def score(y_true, y_pred, **kwargs):
+def score(y_true, y_pred, multiclass=False, **kwargs):
try:
sample_weight = kwargs["0"]
except:
diff --git a/Code/MonoMultiViewClassifiers/ResultAnalysis.py b/Code/MonoMultiViewClassifiers/ResultAnalysis.py
index 64e6a93f..2b72ca9d 100644
--- a/Code/MonoMultiViewClassifiers/ResultAnalysis.py
+++ b/Code/MonoMultiViewClassifiers/ResultAnalysis.py
@@ -218,9 +218,10 @@ def genMetricsScoresMulticlass(results, trueLabels, metrics, argumentsDictionari
for classifierName, resultDictionary in iterResults.items():
if not "metricsScores" in resultDictionary:
results[iterIndex][classifierName]["metricsScores"]={}
- trainScore = metricModule.score(trueLabels[trainIndices],resultDictionary["labels"][trainIndices])
+ trainScore = metricModule.score(trueLabels[trainIndices],resultDictionary["labels"][trainIndices], multiclass=True)
testScore = metricModule.score(trueLabels[multiclassTestIndices],
- resultDictionary["labels"][multiclassTestIndices])
+ resultDictionary["labels"][multiclassTestIndices],
+ multiclass=True)
results[iterIndex][classifierName]["metricsScores"][metric[0]] = [trainScore, testScore]
@@ -720,8 +721,6 @@ def resultAnalysis(benchmark, results, name, times, metrics, directory, minSize=
logging.debug("Done:\t Score graph generation for " + metric[0])
-
-
def analyzeLabels(labelsArrays, realLabels, results, directory, minSize = 10):
"""Used to generate a graph showing errors on each example depending on classifier"""
logging.debug("Start:\t Label analysis figure generation")
@@ -807,7 +806,6 @@ def analyzeIterLabels(labelsAnalysisList, directory, classifiersNames, minSize=1
logging.debug("Done:\t Global error by example figure generation")
-
def genFig(iterResults, metric, nbResults, names, nbMono, minSize=10):
"""Used to generate the bar graph representing the mean scores of each classifiers if multiple iteration
with different random states"""
--
GitLab