RFCT Use model as first argument

This makes a slightly smoother transition to using an object

Author: luispedro

ch02/knn.py

@@ -26,7 +26,7 @@ def plurality(xs):
             return k
 
 # This function was called ``apply_model`` in the first edition
-def predict(features, model):
+def predict(model, features):
     '''Apply k-nn model'''
     k, train_feats, labels = model
     results = []
@@ -42,5 +42,5 @@ def predict(features, model):
 
 
 def accuracy(features, labels, model):
-    preds = predict(features, model)
+    preds = predict(model, features)
     return np.mean(preds == labels)

ch02/threshold.py

@@ -40,7 +40,7 @@ def fit_model(features, labels):
 
 
 # This function was called ``apply_model`` in the first edition
-def predict(features, model):
+def predict(model, features):
     '''Apply a learned model'''
     # A model is a pair as returned by fit_model
     t, fi, reverse = model
@@ -51,5 +51,5 @@ def predict(features, model):
 
 def accuracy(features, labels, model):
     '''Compute the accuracy of the model'''
-    preds = predict(features, model)
+    preds = predict(model, features)
     return np.mean(preds == labels)