v0.1.1

hyperactive/__init__.py

@@ -1,29 +1,9 @@
-"""
-MIT License
+# Author: Simon Blanke
+# Email: [email protected]
+# License: MIT License
 
-Copyright (c) [2018] [Simon Blanke]
-Email: [email protected]
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
-"""
 from .random_search import RandomSearch_Optimizer
 from .simulated_annealing import SimulatedAnnealing_Optimizer
 from .particle_swarm_optimization import ParticleSwarm_Optimizer
 
-__version__ = "0.1"
+__version__ = "0.1.1"

hyperactive/base.py

@@ -14,14 +14,25 @@
 
 
 class BaseOptimizer(object):
-    def __init__(self, search_dict, n_iter, scoring="accuracy", n_jobs=1, cv=5):
+    def __init__(
+        self,
+        search_dict,
+        n_iter,
+        scoring="accuracy",
+        tabu_memory=None,
+        n_jobs=1,
+        cv=5,
+        verbosity=1,
+        random_state=False,
+    ):
         self.search_dict = search_dict
         self.n_iter = n_iter
         self.scoring = scoring
+        self.tabu_memory = tabu_memory
         self.n_jobs = n_jobs
         self.cv = cv
-        self.verbosity = 1
-        self.random_state = None
+        self.verbosity = verbosity
+        self.random_state = random_state
 
         self.X_train = None
         self.y_train = None