clean up

src/DecisionTree.cpp

@@ -93,6 +93,7 @@ string DecisionTree::predictSingle(vector <string>& test, Node *treeRoot, Predic
     }
     Question *question = treeRoot->question;
     int splitIndex = question->splitFeatureIndex;
+    cout<<splitIndex<<endl;
 
     std::pair<int, double> featureInfoGain(question->splitFeatureIndex,
                                            treeRoot->informationGainFromParent);   // value init

src/RandomForest.cpp

@@ -236,6 +236,14 @@ vector <pair<int, double>> sort(map<int, double> &M, vector <string> test, vecto
         cout << features[it.first] << " is " << test[it.first] << ", ";
         count++;
     }
+//    cout<<endl;
+//
+//    cout<<"All explanation: ";
+//    for (auto &it : A) {
+//
+//        cout << features[it.first] << " is " << test[it.first] << ", ";
+//
+//    }
     cout << endl;
     return A;
 }

src/main.cpp

@@ -43,9 +43,9 @@ int main(int argc, char *argv[]) {
     vector <vector<string>> datasetAsString;
     vector <FeatureType> featureTypes;
     vector <string> features;
-    datasetAsString = parseDataToString("../datasets/mnist.data");
-    featureTypes = parseFeatureTypes("../datasets/mnist.featureTypes");
-    features = parseFeatures("../datasets/mnist.features");
+    datasetAsString = parseDataToString("../datasets/adult.data");
+    featureTypes = parseFeatureTypes("../datasets/adult.featureTypes");
+    features = parseFeatures("../datasets/adult.features");
 
     //pick number of features to select for random sub-spacing
     float featureWeight = sqrt(features.size())/features.size();
@@ -81,11 +81,11 @@ int main(int argc, char *argv[]) {
 
 
         cout << endl;
-        cout << "********************* Forest accuracy *****************" << endl;
-        accuracyReport report = randomForest->getAccuracy(datasetAsString,testingIdxs);
-
-        accuracy += report.accuracy;
-        randomForest->printAccuracyReportFile(report);
+//        cout << "********************* Forest accuracy *****************" << endl;
+//        accuracyReport report = randomForest->getAccuracy(datasetAsString,testingIdxs);
+//
+//        accuracy += report.accuracy;
+//        randomForest->printAccuracyReportFile(report);
 
 
         cout << "**************** prediction with explanation ********** " << endl;