diff --git a/src/main/java/ca/joeltherrien/randomforest/Main.java b/src/main/java/ca/joeltherrien/randomforest/Main.java
index 24d96c8..e353c7f 100644
--- a/src/main/java/ca/joeltherrien/randomforest/Main.java
+++ b/src/main/java/ca/joeltherrien/randomforest/Main.java
@@ -28,6 +28,7 @@ import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRi
 import ca.joeltherrien.randomforest.tree.Forest;
 import ca.joeltherrien.randomforest.tree.ForestTrainer;
 import ca.joeltherrien.randomforest.tree.ResponseCombiner;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.utils.StepFunction;
 import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.JsonNodeFactory;
@@ -66,7 +67,7 @@ public class Main {
         final List<Covariate> covariates = settings.getCovariates();
 
         if(args[1].equalsIgnoreCase("train")){
-            final List<Row> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+            final List<Row> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
             final ForestTrainer forestTrainer = new ForestTrainer(settings, dataset, covariates);
 
@@ -111,14 +112,14 @@ public class Main {
                 return;
             }
 
-            final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getValidationDataLocation());
+            final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getValidationDataLocation());
 
             // Let's reduce this down to n
             final int n = Integer.parseInt(args[2]);
             Utils.reduceListToSize(dataset, n, new Random());
 
             final File folder = new File(settings.getSaveTreeLocation());
-            final Forest<?, CompetingRiskFunctions> forest = DataLoader.loadForest(folder, responseCombiner);
+            final Forest<?, CompetingRiskFunctions> forest = DataUtils.loadForest(folder, responseCombiner);
 
             final boolean useBootstrapPredictions = settings.getTrainingDataLocation().equals(settings.getValidationDataLocation());
 
diff --git a/src/main/java/ca/joeltherrien/randomforest/Settings.java b/src/main/java/ca/joeltherrien/randomforest/Settings.java
index 3abccdf..ddffeae 100644
--- a/src/main/java/ca/joeltherrien/randomforest/Settings.java
+++ b/src/main/java/ca/joeltherrien/randomforest/Settings.java
@@ -30,6 +30,7 @@ import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
 import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
 import ca.joeltherrien.randomforest.tree.GroupDifferentiator;
 import ca.joeltherrien.randomforest.tree.ResponseCombiner;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import com.fasterxml.jackson.annotation.JsonIgnore;
 import com.fasterxml.jackson.databind.JsonNode;
 import com.fasterxml.jackson.databind.ObjectMapper;
@@ -55,17 +56,17 @@ import java.util.function.Function;
 @EqualsAndHashCode
 public class Settings {
 
-    private static Map<String, Function<ObjectNode, DataLoader.ResponseLoader>> RESPONSE_LOADER_MAP = new HashMap<>();
-    public static Function<ObjectNode, DataLoader.ResponseLoader> getResponseLoaderConstructor(final String name){
+    private static Map<String, Function<ObjectNode, DataUtils.ResponseLoader>> RESPONSE_LOADER_MAP = new HashMap<>();
+    public static Function<ObjectNode, DataUtils.ResponseLoader> getResponseLoaderConstructor(final String name){
         return RESPONSE_LOADER_MAP.get(name.toLowerCase());
     }
-    public static void registerResponseLoaderConstructor(final String name, final Function<ObjectNode, DataLoader.ResponseLoader> responseLoaderConstructor){
+    public static void registerResponseLoaderConstructor(final String name, final Function<ObjectNode, DataUtils.ResponseLoader> responseLoaderConstructor){
         RESPONSE_LOADER_MAP.put(name.toLowerCase(), responseLoaderConstructor);
     }
 
     static{
         registerResponseLoaderConstructor("double",
-                node -> new DataLoader.DoubleLoader(node)
+                node -> new DataUtils.DoubleLoader(node)
         );
         registerResponseLoaderConstructor("CompetingRiskResponse",
                 node -> new CompetingRiskResponse.CompetingResponseLoader(node)
@@ -238,7 +239,7 @@ public class Settings {
     }
 
     @JsonIgnore
-    public DataLoader.ResponseLoader getResponseLoader(){
+    public DataUtils.ResponseLoader getResponseLoader(){
         final String type = yVarSettings.get("type").asText();
 
         return getResponseLoaderConstructor(type).apply(yVarSettings);
diff --git a/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java
index b4c89ce..e5b7b68 100644
--- a/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java
+++ b/src/main/java/ca/joeltherrien/randomforest/covariates/numeric/NumericCovariate.java
@@ -59,6 +59,13 @@ public final class NumericCovariate implements Covariate<Double> {
                 })
                 .collect(Collectors.toList());
 
+        // It's technically possible for data to be empty now due to NAs which will cause a crash
+        // when we use random.nextInt(maxIndex).
+        if(data.size() == 0){
+            return null;
+        }
+
+
         Iterator<Double> sortedDataIterator = data.stream()
                 .map(row -> row.getCovariateValue(this).getValue())
                 .iterator();
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponse.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponse.java
index d20a8b9..827614b 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponse.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponse.java
@@ -16,7 +16,7 @@
 
 package ca.joeltherrien.randomforest.responses.competingrisk;
 
-import ca.joeltherrien.randomforest.DataLoader;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import com.fasterxml.jackson.databind.node.ObjectNode;
 import lombok.Data;
 import lombok.RequiredArgsConstructor;
@@ -36,7 +36,7 @@ public class CompetingRiskResponse implements Serializable {
 
 
     @RequiredArgsConstructor
-    public static class CompetingResponseLoader implements DataLoader.ResponseLoader<CompetingRiskResponse>{
+    public static class CompetingResponseLoader implements DataUtils.ResponseLoader<CompetingRiskResponse>{
 
         private final String deltaName;
         private final String uName;
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponseWithCensorTime.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponseWithCensorTime.java
index 056a038..f984d38 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponseWithCensorTime.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/CompetingRiskResponseWithCensorTime.java
@@ -16,7 +16,7 @@
 
 package ca.joeltherrien.randomforest.responses.competingrisk;
 
-import ca.joeltherrien.randomforest.DataLoader;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import com.fasterxml.jackson.databind.node.ObjectNode;
 import lombok.Data;
 import lombok.EqualsAndHashCode;
@@ -38,7 +38,7 @@ public final class CompetingRiskResponseWithCensorTime extends CompetingRiskResp
     }
 
     @RequiredArgsConstructor
-    public static class CompetingResponseWithCensorTimeLoader implements DataLoader.ResponseLoader<CompetingRiskResponseWithCensorTime>{
+    public static class CompetingResponseWithCensorTimeLoader implements DataUtils.ResponseLoader<CompetingRiskResponseWithCensorTime>{
 
         private final String deltaName;
         private final String uName;
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/Forest.java b/src/main/java/ca/joeltherrien/randomforest/tree/Forest.java
index 1cc37dc..f82abef 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/Forest.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/Forest.java
@@ -28,6 +28,7 @@ public class Forest<O, FO> { // O = output of trees, FO = forest output. In prac
 
     private final Collection<Tree<O>> trees;
     private final ResponseCombiner<O, FO> treeResponseCombiner;
+    private final List<Covariate> covariateList;
 
     public FO evaluate(CovariateRow row){
 
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java b/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java
index 2e31725..83964aa 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/ForestTrainer.java
@@ -17,18 +17,17 @@
 package ca.joeltherrien.randomforest.tree;
 
 import ca.joeltherrien.randomforest.Bootstrapper;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.Row;
 import ca.joeltherrien.randomforest.Settings;
 import ca.joeltherrien.randomforest.covariates.Covariate;
+import ca.joeltherrien.randomforest.utils.Utils;
 import lombok.AccessLevel;
 import lombok.AllArgsConstructor;
 import lombok.Builder;
 
 import java.io.File;
-import java.io.FileOutputStream;
 import java.io.IOException;
-import java.io.ObjectOutputStream;
-import java.text.NumberFormat;
 import java.util.ArrayList;
 import java.util.List;
 import java.util.Random;
@@ -38,7 +37,6 @@ import java.util.concurrent.ThreadLocalRandom;
 import java.util.concurrent.atomic.AtomicInteger;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
-import java.util.zip.GZIPOutputStream;
 
 @Builder
 @AllArgsConstructor(access=AccessLevel.PRIVATE)
@@ -90,6 +88,7 @@ public class ForestTrainer<Y, TO, FO> {
         return Forest.<TO, FO>builder()
                 .treeResponseCombiner(treeResponseCombiner)
                 .trees(trees)
+                .covariateList(covariates)
                 .build();
 
     }
@@ -112,7 +111,7 @@ public class ForestTrainer<Y, TO, FO> {
                 System.out.print("\rFinished " + treeCount.get() + "/" + ntree + " trees");
             }
 
-            final Runnable worker = new TreeSavedWorker(data, "tree-" + formatNumber(j+1) + ".tree", treeCount);
+            final Runnable worker = new TreeSavedWorker(data, "tree-" + Utils.formatNumber(j+1, ntree) + ".tree", treeCount);
             worker.run();
 
         }
@@ -184,7 +183,7 @@ public class ForestTrainer<Y, TO, FO> {
         final AtomicInteger treeCount = new AtomicInteger(treeFiles.length); // tracks how many trees are finished
 
         for(int j=treeCount.get(); j<ntree; j++){
-            final Runnable worker = new TreeSavedWorker(data, "tree-" + formatNumber(j+1) + ".tree", treeCount);
+            final Runnable worker = new TreeSavedWorker(data, "tree-" + Utils.formatNumber(j+1, ntree) + ".tree", treeCount);
             executorService.execute(worker);
         }
 
@@ -215,16 +214,6 @@ public class ForestTrainer<Y, TO, FO> {
         return treeTrainer.growTree(bootstrappedData, random);
     }
 
-    public void saveTree(final Tree<TO> tree, String name) throws IOException {
-        final String filename = saveTreeLocation + "/" + name;
-
-        final ObjectOutputStream outputStream = new ObjectOutputStream(new GZIPOutputStream(new FileOutputStream(filename)));
-
-        outputStream.writeObject(tree);
-
-        outputStream.close();
-
-    }
 
     private class TreeInMemoryWorker implements Runnable {
 
@@ -250,27 +239,6 @@ public class ForestTrainer<Y, TO, FO> {
         }
     }
 
-    /**
-     * When saving trees we typically save them as tree-1.tree, tree-2.tree. This is fine until we get tree-10.tree, which
-     * when sorted alphabetically goes before tree-2.tree. We should instead save tree-01.tree, ... tree-10.tree.
-     *
-     * We need to set the number of 0s though based on ntree.
-     *
-     * @return
-     */
-    private String formatNumber(int currentTreeNumber){
-        final int numDigits = (int) Math.log10(ntree) + 1;
-
-        String currentTreeNumberString = Integer.toString(currentTreeNumber);
-        final StringBuilder builder = new StringBuilder();
-
-        for(int i=0; i<numDigits-currentTreeNumberString.length(); i++){
-            builder.append('0');
-        }
-        builder.append(currentTreeNumberString);
-
-        return builder.toString();
-    }
 
     private class TreeSavedWorker implements Runnable {
 
@@ -291,7 +259,7 @@ public class ForestTrainer<Y, TO, FO> {
             final Tree<TO> tree = trainTree(bootstrapper, ThreadLocalRandom.current());
 
             try {
-                saveTree(tree, filename);
+                DataUtils.saveObject(tree, saveTreeLocation + "/" + filename);
             } catch (IOException e) {
                 System.err.println("IOException while saving " + filename);
                 e.printStackTrace();
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java
index b0da8ad..8d72efb 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java
@@ -16,6 +16,7 @@
 
 package ca.joeltherrien.randomforest.tree;
 
+import java.io.Serializable;
 import java.util.Iterator;
 
 /**
@@ -26,7 +27,7 @@ import java.util.Iterator;
  *  If you want to implement a very trivial GroupDifferentiator that just takes two Lists as arguments, try extending
  *  SimpleGroupDifferentiator.
  */
-public interface GroupDifferentiator<Y> {
+public interface GroupDifferentiator<Y> extends Serializable {
 
     SplitAndScore<Y, ?> differentiate(Iterator<Split<Y, ?>> splitIterator);
 
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/ResponseCombiner.java b/src/main/java/ca/joeltherrien/randomforest/tree/ResponseCombiner.java
index 66c6821..8bfd277 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/ResponseCombiner.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/ResponseCombiner.java
@@ -16,9 +16,10 @@
 
 package ca.joeltherrien.randomforest.tree;
 
+import java.io.Serializable;
 import java.util.List;
 
-public interface ResponseCombiner<I, O> {
+public interface ResponseCombiner<I, O> extends Serializable {
 
     O combine(List<I> responses);
 
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java b/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java
index b3dba61..fdf4919 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/Tree.java
@@ -57,4 +57,5 @@ public class Tree<Y> implements Node<Y> {
     public String toString(){
         return rootNode.toString();
     }
+
 }
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
index 98292e3..4ce3630 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
@@ -165,6 +165,11 @@ public class TreeTrainer<Y, O> {
         for(final Covariate covariate : covariatesToTry) {
             final Iterator<Split> iterator = covariate.generateSplitRuleUpdater(data, this.numberOfSplits, random);
 
+            // this happens if there were only NA values in data for this covariate. Rare, but I've seen it.
+            if(iterator == null){
+                continue;
+            }
+
             final SplitAndScore<Y, ?> candidateSplitAndScore = noGenericDifferentiator.differentiate(iterator);
 
             if(candidateSplitAndScore != null && (bestSplitAndScore == null ||
diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/DataUtils.java b/src/main/java/ca/joeltherrien/randomforest/utils/DataUtils.java
index bc5ea80..dbe7950 100644
--- a/src/main/java/ca/joeltherrien/randomforest/utils/DataUtils.java
+++ b/src/main/java/ca/joeltherrien/randomforest/utils/DataUtils.java
@@ -14,8 +14,9 @@
  *     along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-package ca.joeltherrien.randomforest;
+package ca.joeltherrien.randomforest.utils;
 
+import ca.joeltherrien.randomforest.Row;
 import ca.joeltherrien.randomforest.covariates.Covariate;
 import ca.joeltherrien.randomforest.tree.Forest;
 import ca.joeltherrien.randomforest.tree.ResponseCombiner;
@@ -98,12 +99,26 @@ public class DataUtils {
 
     }
 
+    public static <O, FO> Forest<O, FO> loadForest(String folder, ResponseCombiner<O, FO> treeResponseCombiner) throws IOException, ClassNotFoundException {
+        final File directory = new File(folder);
+        return loadForest(directory, treeResponseCombiner);
+    }
+
     public static void saveObject(Serializable object, String filename) throws IOException {
         final ObjectOutputStream outputStream = new ObjectOutputStream(new GZIPOutputStream(new FileOutputStream(filename)));
         outputStream.writeObject(object);
         outputStream.close();
     }
 
+    public static Object loadObject(String filename) throws IOException, ClassNotFoundException {
+        final ObjectInputStream inputStream = new ObjectInputStream(new GZIPInputStream(new FileInputStream(filename)));
+        final Object object = inputStream.readObject();
+        inputStream.close();
+
+        return object;
+
+    }
+
     @FunctionalInterface
     public interface ResponseLoader<Y>{
         Y parse(CSVRecord record);
diff --git a/src/main/java/ca/joeltherrien/randomforest/utils/Utils.java b/src/main/java/ca/joeltherrien/randomforest/utils/Utils.java
index a8bc873..7939b86 100644
--- a/src/main/java/ca/joeltherrien/randomforest/utils/Utils.java
+++ b/src/main/java/ca/joeltherrien/randomforest/utils/Utils.java
@@ -208,5 +208,26 @@ public final class Utils {
         return map;
     }
 
+    /**
+     * When saving trees we typically save them as tree-1.tree, tree-2.tree. This is fine until we get tree-10.tree, which
+     * when sorted alphabetically goes before tree-2.tree. We should instead save tree-01.tree, ... tree-10.tree.
+     *
+     * We need to set the number of 0s though based on ntree.
+     *
+     * @return
+     */
+    public static String formatNumber(int currentTreeNumber, int maxNumberOfTrees){
+        final int numDigits = (int) Math.log10(maxNumberOfTrees) + 1;
+
+        String currentTreeNumberString = Integer.toString(currentTreeNumber);
+        final StringBuilder builder = new StringBuilder();
+
+        for(int i=0; i<numDigits-currentTreeNumberString.length(); i++){
+            builder.append('0');
+        }
+        builder.append(currentTreeNumberString);
+
+        return builder.toString();
+    }
 
 }
diff --git a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
index 1d1c486..8a41da2 100644
--- a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
+++ b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
@@ -24,6 +24,7 @@ import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskFunctio
 import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
 import ca.joeltherrien.randomforest.tree.Forest;
 import ca.joeltherrien.randomforest.tree.ForestTrainer;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.utils.Utils;
 import com.fasterxml.jackson.databind.node.*;
 import org.junit.jupiter.api.Test;
@@ -109,7 +110,7 @@ public class TestSavingLoading {
     public void testSavingLoading() throws IOException, ClassNotFoundException {
         final Settings settings = getSettings();
         final List<Covariate> covariates = settings.getCovariates();
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
         final File directory = new File(settings.getSaveTreeLocation());
         assertFalse(directory.exists());
@@ -125,7 +126,7 @@ public class TestSavingLoading {
 
 
 
-        final Forest<CompetingRiskFunctions, CompetingRiskFunctions> forest = DataLoader.loadForest(directory, new CompetingRiskFunctionCombiner(new int[]{1,2}, null));
+        final Forest<CompetingRiskFunctions, CompetingRiskFunctions> forest = DataUtils.loadForest(directory, new CompetingRiskFunctionCombiner(new int[]{1,2}, null));
 
         final CovariateRow predictionRow = getPredictionRow(covariates);
 
diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
index 5e8df31..72c09ce 100644
--- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
+++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
@@ -17,7 +17,7 @@
 package ca.joeltherrien.randomforest.competingrisk;
 
 import ca.joeltherrien.randomforest.CovariateRow;
-import ca.joeltherrien.randomforest.DataLoader;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.Row;
 import ca.joeltherrien.randomforest.Settings;
 import ca.joeltherrien.randomforest.covariates.Covariate;
@@ -126,7 +126,7 @@ public class TestCompetingRisk {
 
         final List<Covariate> covariates = settings.getCovariates();
 
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
         final TreeTrainer<CompetingRiskResponse, CompetingRiskFunctions> treeTrainer = new TreeTrainer<>(settings, covariates);
         final Node<CompetingRiskFunctions> node = treeTrainer.growTree(dataset, new Random());
@@ -179,7 +179,7 @@ public class TestCompetingRisk {
 
         final List<Covariate> covariates = settings.getCovariates();
 
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
         final TreeTrainer<CompetingRiskResponse, CompetingRiskFunctions> treeTrainer = new TreeTrainer<>(settings, covariates);
         final Node<CompetingRiskFunctions> node = treeTrainer.growTree(dataset, new Random());
@@ -229,7 +229,7 @@ public class TestCompetingRisk {
 
         final List<Covariate> covariates = settings.getCovariates();
 
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
         final ForestTrainer<CompetingRiskResponse, CompetingRiskFunctions, CompetingRiskFunctions> forestTrainer = new ForestTrainer<>(settings, dataset, covariates);
 
@@ -277,7 +277,7 @@ public class TestCompetingRisk {
 
         final List<Covariate> covariates = settings.getCovariates();
 
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(), settings.getTrainingDataLocation());
 
         // Let's count the events and make sure the data was correctly read.
         int countCensored = 0;
@@ -320,7 +320,7 @@ public class TestCompetingRisk {
         settings.setNtree(300); // results are too variable at 100
 
         final List<Covariate> covariates = settings.getCovariates();
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(),
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(),
                 settings.getTrainingDataLocation());
         final ForestTrainer<CompetingRiskResponse, CompetingRiskFunctions, CompetingRiskFunctions> forestTrainer = new ForestTrainer<>(settings, dataset, covariates);
 
@@ -341,7 +341,7 @@ public class TestCompetingRisk {
         settings.setNtree(300); // results are too variable at 100
 
         final List<Covariate> covariates = settings.getCovariates();
-        final List<Row<CompetingRiskResponse>> dataset = DataLoader.loadData(covariates, settings.getResponseLoader(),
+        final List<Row<CompetingRiskResponse>> dataset = DataUtils.loadData(covariates, settings.getResponseLoader(),
                 settings.getTrainingDataLocation());
         final ForestTrainer<CompetingRiskResponse, CompetingRiskFunctions, CompetingRiskFunctions> forestTrainer = new ForestTrainer<>(settings, dataset, covariates);
         final Forest<CompetingRiskFunctions, CompetingRiskFunctions> forest = forestTrainer.trainSerial();
diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java
index ada9ec0..ddb56d9 100644
--- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java
+++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankMultipleGroupDifferentiator.java
@@ -16,7 +16,7 @@
 
 package ca.joeltherrien.randomforest.competingrisk;
 
-import ca.joeltherrien.randomforest.DataLoader;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.Row;
 import ca.joeltherrien.randomforest.Settings;
 import ca.joeltherrien.randomforest.covariates.Covariate;
@@ -36,7 +36,6 @@ import java.io.IOException;
 import java.util.Collections;
 import java.util.Iterator;
 import java.util.List;
-import java.util.stream.Collectors;
 
 import static org.junit.jupiter.api.Assertions.assertTrue;
 
@@ -63,8 +62,8 @@ public class TestLogRankMultipleGroupDifferentiator {
 
         final List<Covariate> covariates = settings.getCovariates();
 
-        final DataLoader.ResponseLoader loader = settings.getResponseLoader();
-        final List<Row<CompetingRiskResponse>> rows = DataLoader.loadData(covariates, loader, settings.getTrainingDataLocation());
+        final DataUtils.ResponseLoader loader = settings.getResponseLoader();
+        final List<Row<CompetingRiskResponse>> rows = DataUtils.loadData(covariates, loader, settings.getTrainingDataLocation());
 
         return new Data<>(rows, covariates);
     }
diff --git a/src/test/java/ca/joeltherrien/randomforest/covariates/NumericCovariateTest.java b/src/test/java/ca/joeltherrien/randomforest/covariates/NumericCovariateTest.java
index 2af5ebe..282d9d7 100644
--- a/src/test/java/ca/joeltherrien/randomforest/covariates/NumericCovariateTest.java
+++ b/src/test/java/ca/joeltherrien/randomforest/covariates/NumericCovariateTest.java
@@ -35,6 +35,23 @@ public class NumericCovariateTest {
         return rowList;
     }
 
+    private List<Row<Double>> createTestDatasetMissingValues(NumericCovariate covariate){
+        final List<Row<Double>> rowList = new ArrayList<>();
+        final List<Covariate> covariateList = Collections.singletonList(covariate);
+
+        final String naString = "NA";
+
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 1, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 2, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 3, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 4, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 5, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 6, 1.0));
+        rowList.add(Row.createSimple(Utils.easyMap("x", naString), covariateList, 7, 1.0));
+
+        return rowList;
+    }
+
     @Test
     public void testNumericCovariateDeterministic(){
         final NumericCovariate covariate = new NumericCovariate("x", 0);
@@ -184,6 +201,21 @@ public class NumericCovariateTest {
 
     }
 
+    /**
+     * If all the values are missing on a covariate then we shouldn't return an iterator.
+     *
+     */
+    @Test
+    public void testNumericSplitRuleUpdaterWithIndexesAllMissingData(){
+        final NumericCovariate covariate = new NumericCovariate("x", 0);
+        final List<Row<Double>> dataset = createTestDatasetMissingValues(covariate);
+        final NumericSplitRuleUpdater<Double> updater = covariate.generateSplitRuleUpdater(dataset, 5, new Random());
+
+        assertNull(updater);
+    }
+
+
+
     private <T> void assertContains(List<T> subList, List<T> greaterList){
         boolean allContained = true;
 
diff --git a/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java b/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java
index 4be6f51..ac5dc13 100644
--- a/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java
+++ b/src/test/java/ca/joeltherrien/randomforest/csv/TestLoadingCSV.java
@@ -16,7 +16,7 @@
 
 package ca.joeltherrien.randomforest.csv;
 
-import ca.joeltherrien.randomforest.DataLoader;
+import ca.joeltherrien.randomforest.utils.DataUtils;
 import ca.joeltherrien.randomforest.Row;
 import ca.joeltherrien.randomforest.Settings;
 import ca.joeltherrien.randomforest.covariates.settings.BooleanCovariateSettings;
@@ -64,9 +64,9 @@ public class TestLoadingCSV {
         final List<Covariate> covariates = settings.getCovariates();
 
 
-        final DataLoader.ResponseLoader loader = settings.getResponseLoader();
+        final DataUtils.ResponseLoader loader = settings.getResponseLoader();
 
-        return DataLoader.loadData(covariates, loader, settings.getTrainingDataLocation());
+        return DataUtils.loadData(covariates, loader, settings.getTrainingDataLocation());
     }
 
     @Test