From 9b7f991611b84d870b4f02d0e5783033183650c2 Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin@lis-lab.fr>
Date: Tue, 2 Apr 2019 11:49:37 -0400
Subject: [PATCH] Debugged sparsity scm from placeholder
---
.../MonoviewClassifiers/SCMPregen.py | 2 ++
.../MonoviewClassifiers/SCMPregenTree.py | 2 ++
.../MonoviewClassifiers/SCMSparsity.py | 6 ++++--
.../MonoviewClassifiers/SCMSparsityTree.py | 4 +++-
4 files changed, 11 insertions(+), 3 deletions(-)
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py
index dd6224cf..f4b6df25 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregen.py
@@ -40,6 +40,7 @@ class SCMPregen(scm, BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
@@ -57,6 +58,7 @@ class SCMPregen(scm, BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py
index 6634bb5a..5ead0cf9 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMPregenTree.py
@@ -42,6 +42,7 @@ class SCMPregenTree(scm, BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
@@ -59,6 +60,7 @@ class SCMPregenTree(scm, BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py
index 27745be1..83c757f7 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsity.py
@@ -16,7 +16,7 @@ __status__ = "Prototype" # Production, Development, Prototype
class SCMSparsity(BaseMonoviewClassifier, PregenClassifier):
- def __init__(self, random_state=None, model_type="conjunction",
+ def __init__(self, random_state=None, model_type="disjunction",
max_rules=10, p=0.1, n_stumps=1, self_complemented=True, **kwargs):
self.scm_estimators = [scm(
random_state=random_state,
@@ -49,6 +49,7 @@ class SCMSparsity(BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
@@ -59,7 +60,7 @@ class SCMSparsity(BaseMonoviewClassifier, PregenClassifier):
scm_estimator.fit(place_holder, y, tiebreaker=None, iteration_callback=None, **fit_params)
end = time.time()
self.times = np.array([end-beg, 0])
- self.train_metrics = [zero_one_loss.score(y, scm_estimator.predict(X)) for scm_estimator in self.scm_estimators]
+ self.train_metrics = [zero_one_loss.score(y, scm_estimator.predict(place_holder)) for scm_estimator in self.scm_estimators]
return self.scm_estimators[-1]
def predict(self, X):
@@ -71,6 +72,7 @@ class SCMSparsity(BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py
index e28a99f1..bb271733 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/SCMSparsityTree.py
@@ -49,6 +49,7 @@ class SCMSparsityTree(BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
@@ -59,7 +60,7 @@ class SCMSparsityTree(BaseMonoviewClassifier, PregenClassifier):
scm_estimator.fit(place_holder, y, tiebreaker=None, iteration_callback=None, **fit_params)
end = time.time()
self.times = np.array([end-beg, 0])
- self.train_metrics = [zero_one_loss.score(y, scm_estimator.predict(X)) for scm_estimator in self.scm_estimators]
+ self.train_metrics = [zero_one_loss.score(y, scm_estimator.predict(place_holder)) for scm_estimator in self.scm_estimators]
return self.scm_estimators[-1]
def predict(self, X):
@@ -71,6 +72,7 @@ class SCMSparsityTree(BaseMonoviewClassifier, PregenClassifier):
file_name = "pregen_x" + str(a) + ".csv"
while file_name in list_files:
a = int(np.random.randint(0, 10000))
+ file_name = "pregen_x" + str(a) + ".csv"
else:
file_name = "pregen_x"+str(a)+".csv"
np.savetxt(file_name, pregen_X, delimiter=',')
--
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