diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
index f5191941440f620e4f3665bf996f0d6378e1b4c0..3f1e4c4e868988693b2c5199f5e1e1716a6ee7b6 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/BoostUtils.py
@@ -696,7 +696,7 @@ def get_accuracy_graph(train_accuracies, classifier_name, file_name, name="Accur
class BaseBoost(object):
def __init__(self):
- self.n_stumps = 1
+ self.n_stumps_per_attribute = 1
def _collect_probas(self, X):
return np.asarray([clf.predict_proba(X) for clf in self.estimators_generator.estimators_])
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py
index c7ebf500968c67104e7f1e4594a26352c6286e46..f5ba4681e3b27c3ed730cf5f14e408ed2813d547 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/CQBoostUtils.py
@@ -32,7 +32,7 @@ class ColumnGenerationClassifier(BaseEstimator, ClassifierMixin, BaseBoost):
y[y == 0] = -1
if self.estimators_generator is None:
- self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps, self_complemented=True)
+ self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps_per_attribute, self_complemented=True)
self.estimators_generator.fit(X, y)
self.classification_matrix = self._binary_classification_matrix(X)
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
index 5fdb396fd98608cc0464e661b3f188cc441b02f9..f684a51804deddd1f848aab7c5253d1486963bfe 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/Additions/QarBoostUtils.py
@@ -6,7 +6,6 @@ from collections import defaultdict
import math
from sklearn.utils.validation import check_is_fitted
from sklearn.base import BaseEstimator, ClassifierMixin
-from sklearn.metrics import accuracy_score
import time
import matplotlib.pyplot as plt
@@ -15,19 +14,18 @@ from ... import Metrics
class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
- def __init__(self, n_max_iterations=350, estimators_generator=None, dual_constraint_rhs=0,
+ def __init__(self, n_max_iterations=350, estimators_generator=None,
random_state=42, self_complemented=True, twice_the_same=False, old_fashioned=False,
previous_vote_weighted=True, c_bound_choice = True, random_start = True,
- two_wieghts_problem=False, divided_ponderation=True, n_stumps_per_attribute=None):
+ two_wieghts_problem=False, divided_ponderation=True, n_stumps_per_attribute=None, use_r=True, plotted_metric=Metrics.zero_one_loss):
super(ColumnGenerationClassifierQar, self).__init__()
self.n_max_iterations = n_max_iterations
self.estimators_generator = estimators_generator
- self.dual_constraint_rhs = dual_constraint_rhs
if type(random_state) is int:
self.random_state = np.random.RandomState(random_state)
else:
self.random_state = random_state
- self.self_complemented =self_complemented
+ self.self_complemented = self_complemented
self.twice_the_same = twice_the_same
self.train_time = 0
self.old_fashioned = old_fashioned
@@ -36,13 +34,13 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
self.random_start = random_start
self.two_wieghts_problem = two_wieghts_problem
self.divided_ponderation = divided_ponderation
- self.plotted_metric = Metrics.zero_one_loss
+ self.plotted_metric = plotted_metric
if n_stumps_per_attribute:
- self.n_stumps = n_stumps_per_attribute
-
+ self.n_stumps_per_attribute = n_stumps_per_attribute
+ self.use_r = use_r
self.printed_args_name_list = ["n_max_iterations", "self_complemented", "twice_the_same", "old_fashioned",
"previous_vote_weighted", "c_bound_choice", "random_start",
- "two_wieghts_problem", "divided_ponderation", "n_stumps"]
+ "two_wieghts_problem", "divided_ponderation", "n_stumps", "use_r"]
def set_params(self, **params):
self.self_complemented = params["self_complemented"]
@@ -60,7 +58,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
X = np.array(X.todense())
if self.estimators_generator is None:
- self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps,
+ self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps_per_attribute,
self_complemented=self.self_complemented)
# Initialization
y[y == 0] = -1
@@ -93,7 +91,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
self.n_total_hypotheses_ = n
self.n_total_examples = m
- self.n_max_iterations = 100
+ self.n_max_iterations = n
self.break_cause = " the maximum number of iterations was attained."
for k in range(min(n, self.n_max_iterations if self.n_max_iterations is not None else np.inf)):
@@ -134,14 +132,24 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
# Generate the new weight for the new voter
epsilon = self._compute_epsilon(y)
self.epsilons.append(epsilon)
+
+ r = self._compute_r(y)
+
if epsilon == 0. or math.log((1 - epsilon) / epsilon) == math.inf:
self.chosen_columns_.pop()
self.break_cause = " epsilon was too small."
break
+
if self.divided_ponderation:
- self.q = (1/(self.n_max_iterations-k))*math.log((1 - epsilon) / epsilon)
+ if self.use_r:
+ self.q = (1 / (self.n_max_iterations - k)) * 0.5*math.log((1+r)/(1-r))
+ else:
+ self.q = (1/(self.n_max_iterations-k))*math.log((1 - epsilon) / epsilon)
else:
- self.q = math.log((1 - epsilon) / epsilon)
+ if self.use_r:
+ self.q = 0.5*math.log((1+r)/(1-r))
+ else:
+ self.q = math.log((1 - epsilon) / epsilon)
self.weights_.append(self.q)
# Update the distribution on the examples.
@@ -156,7 +164,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
self.previous_margins.append(np.multiply(y, self.previous_vote))
self.train_metrics.append(self.plotted_metric.score(y, np.sign(self.previous_vote)))
# self.bounds.append(np.prod(np.sqrt(1-4*np.square(0.5-np.array(self.epsilons)))))
- r = self._compute_r(y)
+
if k!=0:
self.bounds.append(self.bounds[-1]*math.sqrt(1-r**2))
else:
@@ -322,7 +330,7 @@ class ColumnGenerationClassifierQar(BaseEstimator, ClassifierMixin, BaseBoost):
if C1 == 0:
return ['break', "the derivate was constant"]
else :
- is_acceptable, sol = self._analyze_solutions_one_weight(np.array(float(C0)/C1))
+ is_acceptable, sol = self._analyze_solutions_one_weight(np.array(float(C0)/C1).reshape((1,1)))
if is_acceptable:
return np.array([sol])
try:
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py
index 9274d9dc11ecaff6c5d107c20f305176650626f7..f5b0ba94ef828e6dc505dd4ab09eb4f86a5b80ae 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/CQBoostv21.py
@@ -28,7 +28,7 @@ class ColumnGenerationClassifierv21(BaseEstimator, ClassifierMixin, BaseBoost):
X = np.array(X.todense())
if self.estimators_generator is None:
- self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps, self_complemented=True)
+ self.estimators_generator = StumpsClassifiersGenerator(n_stumps_per_attribute=self.n_stumps_per_attribute, self_complemented=True)
y[y == 0] = -1
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py
index 34dc7bb0ff662f5badadbd7367d6f6c939a4818f..0279ac4ac9080013e76dcb6842a9559e84487ca9 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC.py
@@ -3,7 +3,6 @@ from ..Monoview.Additions.BoostUtils import getInterpretBase
from ..Monoview.Additions.QarBoostUtils import ColumnGenerationClassifierQar
-
class QarBoostNC(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
def __init__(self, random_state=None, **kwargs):
@@ -13,11 +12,12 @@ class QarBoostNC(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
twice_the_same=False,
old_fashioned=False,
previous_vote_weighted=False,
- c_bound_choice=False,
- random_start=True,
- two_wieghts_problem=True,
+ c_bound_choice=True,
+ random_start=False,
+ two_wieghts_problem=False,
divided_ponderation=False,
- n_stumps_per_attribute=100
+ n_stumps_per_attribute=1,
+ use_r=True
)
self.param_names = []
self.distribs = []
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC2.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC2.py
index dac1ca07d01ea532b201f753e496072a80be5b06..2739affea598beee878ca939fc8d7393172d1047 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC2.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC2.py
@@ -8,14 +8,16 @@ class QarBoostNC2(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
def __init__(self, random_state=None, **kwargs):
super(QarBoostNC2, self).__init__(
random_state=random_state,
- self_complemented=False,
+ self_complemented=True,
twice_the_same=False,
old_fashioned=False,
previous_vote_weighted=False,
c_bound_choice=True,
random_start=True,
two_wieghts_problem=False,
- divided_ponderation=True
+ divided_ponderation=False,
+ n_stumps_per_attribute=10,
+ use_r=True
)
self.param_names = []
self.distribs = []
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py
index dbafa810e61f52c47c0ae9e2c2e592b770e00289..7cb49df54f584f395117f33368386c7e401887ca 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostNC3.py
@@ -15,8 +15,9 @@ class QarBoostNC3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
c_bound_choice=True,
random_start=True,
two_wieghts_problem=False,
- divided_ponderation=False,
- n_stumps_per_attribute=10
+ divided_ponderation=True,
+ n_stumps_per_attribute=1,
+ use_r=True
)
self.param_names = []
self.distribs = []
@@ -31,7 +32,7 @@ class QarBoostNC3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
return self.getInterpretQar(directory)
def get_name_for_fusion(self):
- return "QBN2"
+ return "QBN3"
def formatCmdArgs(args):
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py
index e72688f6c8f7ec97363792631d283e14a2cd42e9..7fb2239a9f8fc71c09d1ac70604adf73c5cc702c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv2.py
@@ -8,15 +8,16 @@ class QarBoostv2(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
def __init__(self, random_state=None, **kwargs):
super(QarBoostv2, self).__init__(
random_state=random_state,
- self_complemented=True,
+ self_complemented=False,
twice_the_same=False,
old_fashioned=False,
previous_vote_weighted=False,
c_bound_choice=True,
- random_start=True,
+ random_start=False,
two_wieghts_problem=False,
divided_ponderation=False,
- n_stumps_per_attribute=10
+ n_stumps_per_attribute=1,
+ use_r=True
)
self.param_names = []
self.distribs = []
@@ -28,7 +29,7 @@ class QarBoostv2(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
return True
def getInterpret(self, directory):
- return getInterpretBase(self, directory, "QarBoostv2", self.weights_, self.break_cause)
+ return self.getInterpretQar(directory)
def get_name_for_fusion(self):
return "QBv2"
diff --git a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py
index 7b63ea7597fb8117f901281aaba0415468b18c7e..aca342a5ed3fd6483581a1eb86df97e1cea3ad9c 100644
--- a/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py
+++ b/multiview_platform/MonoMultiViewClassifiers/MonoviewClassifiers/QarBoostv3.py
@@ -8,15 +8,16 @@ class QarBoostv3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
def __init__(self, random_state=None, **kwargs):
super(QarBoostv3, self).__init__(
random_state=random_state,
- self_complemented=True,
+ self_complemented=False,
twice_the_same=False,
old_fashioned=False,
previous_vote_weighted=False,
c_bound_choice=True,
random_start=True,
two_wieghts_problem=False,
- divided_ponderation=False,
- n_stumps_per_attribute=1
+ divided_ponderation=True,
+ n_stumps_per_attribute=1,
+ use_r=False
)
self.param_names = []
self.distribs = []
@@ -28,7 +29,7 @@ class QarBoostv3(ColumnGenerationClassifierQar, BaseMonoviewClassifier):
return True
def getInterpret(self, directory):
- return getInterpretBase(self, directory, "QarBoostv3", self.weights_, self.break_cause)
+ return self.getInterpretQar(directory)
def get_name_for_fusion(self):
return "QBv3"