Added new config file

PRL/prl.py

@@ -421,6 +421,13 @@ def fit(self, iterations=1000, verbose=False):
 
 
     def predict(self, gen_pref_test):
+        """Computes the classification for the given test preferences.
+
+        :param gen_pref_test: test preference generator
+        :type gen_pref_test: object of class which inherits from <:genP.GenP>, e.g., GenMacroP
+        :returns: a vector containing the predictions
+        :rtype: numpy.ndarray
+        """
         X = gen_pref_test.X
         y_pred = []
         for i in range(gen_pref_test.n):

config/config.json

@@ -3,8 +3,8 @@
     "feat_gen" : "GenHPolyF",
     "feat_gen_params" : [3],
     "pref_generator" : "macro",
-    "columns_budget" : 1000,
-    "iterations" : 10,
-    "solver" : "LinProg",
-    "solver_params" : [0]
+    "columns_budget" : 500,
+    "iterations" : 100,
+    "solver" : "FictitiousPlay",
+    "solver_params" : [1000000]
 }

config/config_kprl.json

@@ -0,0 +1,10 @@
+{
+    "algorithm": "KPRL",
+    "kernel_gen" : "GenHPK",
+    "kernel_gen_params" : [1,3],
+    "pref_generator" : "macro",
+    "columns_budget" : 500,
+    "iterations" : 100,
+    "solver" : "FictitiousPlay",
+    "solver_params" : [1000000]
+}

run_prl.py

@@ -65,11 +65,9 @@ def manage_options():
     Xtr = scaler.transform(Xtr)
     Xte = scaler.transform(Xte)
 elif options["normalize"] == 2:
-    print("here")
     Xtr = normalize(Xtr)
     Xte = normalize(Xte)
 #
-print(Xtr[0,:])
 
 #LOAD CONFIGURATION FILE
 with open(options['config_file'], "r") as f: