add: expected error reduction almost implemented

Author: cosmic-cortex

modAL/expected_error_reduction.py

@@ -0,0 +1,37 @@
+"""
+Expected error reduction framework for active learning.
+"""
+
+from typing import Tuple
+
+import numpy as np
+
+from scipy.stats import entropy
+from sklearn.base import clone
+
+from modAL.models import ActiveLearner
+from modAL.utils.data import modALinput, data_vstack
+from modAL.utils.selection import multi_argmax
+
+
+def expected_error_reduction(classifier: ActiveLearner, X: modALinput,
+                             p_subsample=1.0: np.float, n_instances=1: int) -> Tuple[np.ndarray, modALinput]:
+
+    expected_error = np.full(shape=(len(X), ), fill_value=-np.nan)
+    possible_labels = np.unique(classifier.y_training)
+
+    for x_idx, x in enumerate(X):
+        # subsample the data if needed
+        if np.random.rand() <= p_subsample:
+            # estimate the expected error
+            for y in possible_labels:
+                X_new = data_vstack((classifier.X_training, x))
+                y_new = None
+
+                refitted_estimator = clone(classifier.estimator).fit()
+
+
+    query_idx = multi_argmax(expected_error, n_instances)
+
+    return query_idx, X[query_idx]
+