modAL.acquisition UCB implemented

Author: cosmic-cortex

modAL/__init__.py

@@ -1,5 +1,5 @@
 from .models import ActiveLearner, Committee, CommitteeRegressor
-from .acquisition import PI, max_PI
+from .acquisition import PI, EI, UCB, max_PI, max_EI, max_UCB
 from .uncertainty import classifier_uncertainty, classifier_margin, classifier_entropy, \
                          uncertainty_sampling, margin_sampling, entropy_sampling
 from .disagreement import vote_entropy, consensus_entropy, KL_max_disagreement, \
@@ -8,7 +8,7 @@
 
 __all__ = [
     'ActiveLearner', 'Committee', 'CommitteeRegressor',
-    'PI', 'max_PI',
+    'PI', 'EI', 'UCB', 'max_PI', 'max_EI', 'max_UCB',
     'classifier_uncertainty', 'classifier_margin', 'classifier_entropy',
     'uncertainty_sampling', 'margin_sampling', 'entropy_sampling',
     'vote_entropy', 'consensus_entropy', 'KL_max_disagreement',

modAL/acquisition.py

@@ -25,6 +25,15 @@ def EI(optimizer, X, tradeoff=0):
     return (mean - optimizer.max_val - tradeoff)*ndtr(z) + std*norm.pdf(z)
 
 
+def UCB(optimizer, X, beta=1):
+    """
+    Ref: https://arxiv.org/abs/0912.3995
+    """
+    mean, std = optimizer.predict(X, return_std=True)
+
+    return mean + beta*std
+
+
 def max_PI(optimizer, X, tradeoff=0, n_instances=1):
     pi = PI(optimizer, X, tradeoff=tradeoff)
     query_idx = multi_argmax(pi, n_instances=n_instances)
@@ -37,3 +46,10 @@ def max_EI(optimizer, X, tradeoff=0, n_instances=1):
     query_idx = multi_argmax(ei, n_instances=n_instances)
 
     return query_idx, X[query_idx]
+
+
+def max_UCB(optimizer, X, beta=0, n_instances=1):
+    ucb = UCB(optimizer, X, beta=beta)
+    query_idx = multi_argmax(ucb, n_instances=n_instances)
+
+    return query_idx, X[query_idx]