Adding Local Adaptive Streaming Tree (#1610)

* add first last with out-of-date docs

* update LAST to detect change in the data distribution + iter_arff none class

Docs are also updated

* update docs

* Update hoeffding_adaptive_tree_classifier.py

* changes after tests

* solving inheritance and small fixes

* tests + current_merit method

* Update river/tree/hoeffding_adaptive_tree_classifier.py

* update docs

* change docs

* change last

* Update docs/releases/unreleased.md

* Update river/tree/hoeffding_adaptive_tree_classifier.py

* Update river/tree/last_classifier.py

* add disclamer

* Update river/tree/last_classifier.py

---------

Co-authored-by: Saulo Martiello Mastelini <[email protected]>

Author: danielnowakassis

docs/releases/unreleased.md

@@ -17,3 +17,9 @@
 ## tree
 
 - Instead of letting trees grow indefinitely, setting the `max_depth` parameter to `None` will stop the trees from growing when they reach the system recursion limit.
+
+-Added `tree.LASTClassifier` (Local Adaptive Streaming Tree Classifier).
+
+## stream
+
+- `stream.iter_arff` now supports blank values (treated as missing values).

river/stream/iter_arff.py

@@ -176,7 +176,7 @@ def iter_arff(
             x = {
                 name: cast(val) if cast else val
                 for name, cast, val in zip(names, casts, r.rstrip().split(","))
-                if val != "?"
+                if val != "?" and val != ""
             }
 
         # Handle target
@@ -185,7 +185,10 @@ def iter_arff(
             if isinstance(target, list):
                 y = {name: x.pop(name, 0) for name in target}
             else:
-                y = x.pop(target) if target else None
+                try:
+                    y = x.pop(target) if target else None
+                except KeyError:
+                    y = None
 
         yield x, y
 

river/tree/__init__.py

@@ -59,6 +59,7 @@
 from .hoeffding_tree_classifier import HoeffdingTreeClassifier
 from .hoeffding_tree_regressor import HoeffdingTreeRegressor
 from .isoup_tree_regressor import iSOUPTreeRegressor
+from .last_classifier import LASTClassifier
 from .stochastic_gradient_tree import SGTClassifier, SGTRegressor
 
 __all__ = [
@@ -70,6 +71,7 @@
     "HoeffdingTreeRegressor",
     "HoeffdingAdaptiveTreeRegressor",
     "iSOUPTreeRegressor",
+    "LASTClassifier",
     "SGTClassifier",
     "SGTRegressor",
 ]