Finish first version of DTLearner. Needs testing.

assess_learners/testlearner.py

@@ -52,18 +52,15 @@ if __name__=="__main__":
     testX = data[train_rows:,0:-1]
     testY = data[train_rows:,-1]
 
-    # print(f"{testX.shape}")
-    # print(f"{testY.shape}")
+    print(f"{testX.shape}")
+    print(f"{testY.shape}")
 
     # create a learner and train it
     # learner = lrl.LinRegLearner(verbose = True) # create a LinRegLearner
     learner = dtl.DTLearner(verbose = True) # create a LinRegLearner
-    # learner.addEvidence(trainX, trainY) # train it #XXX split back into test and non-test
-    learner.addEvidence(data[:,0:-1], data[:,-1])
+    learner.addEvidence(trainX, trainY)
     print(learner.author())
 
-    sys.exit(0)
-
     # evaluate in sample
     predY = learner.query(trainX) # get the predictions
     rmse = math.sqrt(((trainY - predY) ** 2).sum()/trainY.shape[0])