add type casting to ATM hyperparameters

atm/method.py

@@ -1,3 +1,5 @@
+from builtins import object, str as newstr
+
 import json
 from os.path import join
 
@@ -33,6 +35,20 @@ class Categorical(HyperParameter):
     def __init__(self, name, type, values):
         self.name = name
         self.type = type
+        for i, val in enumerate(values):
+            if val is None:
+                # the value None is allowed for every parameter type
+                continue
+            if self.type == 'int_cat':
+                values[i] = int(val)
+            elif self.type == 'float_cat':
+                values[i] = float(val)
+            elif self.type == 'string':
+                # this is necessary to avoid a bug in sklearn, which won't be
+                # fixed until 0.20
+                values[i] = str(newstr(val))
+            elif self.type == 'bool':
+                values[i] = bool(val)
         self.values = values
 
     @property

methods/stochastic_gradient_descent.json

@@ -19,7 +19,7 @@
             "range": [0.0, 1.0]
         },
         "fit_intercept": {
-            "type": "int_cat",
+            "type": "int",
             "range": [0, 1]
         },
         "n_iter": {

methods/support_vector_machine.json

@@ -36,7 +36,7 @@
         },
         "class_weight": {
             "type": "string",
-            "range": ["balanced"]
+            "values": ["balanced"]
         },
         "_scale": {
             "type": "bool",