SVM Example Fixes

examples/svm/svm.py

@@ -12,6 +12,7 @@
 # imported: as long as the module we want exists on the worker, it can be
 # imported and used.
 import numpy as np
+import sklearn
 from sklearn.svm import SVC
 from sklearn.ensemble import BaggingClassifier
 from sklearn.multiclass import OneVsRestClassifier
@@ -58,6 +59,7 @@ def main(params):
     out : dict
         Dictionary of performance metrics to send to SHADHO.
     """
+
     # Extract the kernel name and parameters. This is just a short expression
     # to get the only dictionary entry, which should have our hyperparameters.
     kernel_params = list(params.values())[0]
@@ -68,14 +70,8 @@ def main(params):
     X_train = X_train.astype(np.float32) / 255.0
     X_test = X_test.astype(np.float32) / 255.0
 
-    # Set up the SVM with its parameterized kernel. The long form of instantiation
-    # is done here to show what `kernel_params` looks like internally.
-    # This can be shortened to `svc = SVC(**kernel_params)`
-    svc = SVC(kernel=kernel_params['kernel'],
-              C=kernel_params['C'],
-              gamma=kernel_params['gamma'] if 'gamma' in kernel_params else None,
-              coef0=kernel_params['coef0'] if 'coef0' in kernel_params else None,
-              degree=kernel_params['degree'] if 'degree' in kernel_params else None)
+    # Set up the SVM with its parameterized kernel.
+    svc = SVC(**kernel_params)
 
     # Set up parallel training across as many cores as are available on the
     # worker.
@@ -94,7 +90,7 @@ def main(params):
     # Generate and encode testing set predictions, along with prediction time.
     start = time.time()
     predictions = s.predict(X_test)
-    test_time = time.time()
+    test_time = time.time() - start
     encoder = LabelBinarizer()
     loss_labels = encoder.fit_transform(predictions)
 
@@ -113,7 +109,7 @@ def main(params):
         'accuracy': acc,
         'precision': p,
         'recall': r,
-        'params': svm,
+        'params': kernel_params,
         'train_time': train_time,
         'test_time': test_time
     }

shadho/spaces.py

@@ -1,4 +1,4 @@
-from shadho.scaling import linear, ln, log_10, log_2
+from .scaling import linear, ln, log_10, log_2
 
 from pyrameter import Scope, ContinuousDomain, DiscreteDomain
 import scipy.stats