Finish all learners, but they don't pass tests. I have to figure out why they perform so bad.

assess_learners/testlearner.py

@@ -26,6 +26,9 @@ import numpy as np
 import math
 import LinRegLearner as lrl
 import DTLearner as dtl
+import RTLearner as rtl
+import BagLearner as bgl
+import InsaneLearner as isl
 import sys
 
 if __name__=="__main__":
@@ -36,11 +39,7 @@ if __name__=="__main__":
     # data = np.array([list(map(float,s.strip().split(',')[1:]))
                      # for s in inf.readlines()[1:]])
     data = np.array([list(map(float,s.strip().split(',')[1:]))
-                     for s in inf.readlines()])
-
-    # XXX: Get rid of some rows and columns for easier development.
-    # XXX: Remove later for testing!
-    # data = data[:10,5:]
+                     for s in inf.readlines()[1:]])
 
     # compute how much of the data is training and testing
     train_rows = int(0.6* data.shape[0])
@@ -58,6 +57,9 @@ if __name__=="__main__":
     # create a learner and train it
     # learner = lrl.LinRegLearner(verbose = True) # create a LinRegLearner
     learner = dtl.DTLearner(verbose = True) # create a LinRegLearner
+    # learner = rtl.RTLearner(verbose = True) # create a LinRegLearner
+    # learner = bgl.BagLearner(dtl.DTLearner, bags=50) # create a LinRegLearner
+    # learner = isl.InsaneLearner()
     learner.addEvidence(trainX, trainY)
     print(learner.author())