diff --git a/src/main/java/ca/joeltherrien/randomforest/Main.java b/src/main/java/ca/joeltherrien/randomforest/Main.java
index e353c7f..3aa29ab 100644
--- a/src/main/java/ca/joeltherrien/randomforest/Main.java
+++ b/src/main/java/ca/joeltherrien/randomforest/Main.java
@@ -180,8 +180,8 @@ public class Main {
private static Settings defaultTemplate(){
- final ObjectNode groupDifferentiatorSettings = new ObjectNode(JsonNodeFactory.instance);
- groupDifferentiatorSettings.set("type", new TextNode("WeightedVarianceGroupDifferentiator"));
+ final ObjectNode splitFinderSettings = new ObjectNode(JsonNodeFactory.instance);
+ splitFinderSettings.set("type", new TextNode("WeightedVarianceSplitFinder"));
final ObjectNode responseCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
responseCombinerSettings.set("type", new TextNode("MeanResponseCombiner"));
@@ -204,7 +204,7 @@ public class Main {
.validationDataLocation("validation_data.csv")
.responseCombinerSettings(responseCombinerSettings)
.treeCombinerSettings(treeCombinerSettings)
- .groupDifferentiatorSettings(groupDifferentiatorSettings)
+ .splitFinderSettings(splitFinderSettings)
.yVarSettings(yVarSettings)
.maxNodeDepth(100000)
.mtry(2)
diff --git a/src/main/java/ca/joeltherrien/randomforest/Settings.java b/src/main/java/ca/joeltherrien/randomforest/Settings.java
index da83ff4..64bd8da 100644
--- a/src/main/java/ca/joeltherrien/randomforest/Settings.java
+++ b/src/main/java/ca/joeltherrien/randomforest/Settings.java
@@ -22,11 +22,11 @@ import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskRespons
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponseWithCensorTime;
import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskFunctionCombiner;
import ca.joeltherrien.randomforest.responses.competingrisk.combiner.CompetingRiskResponseCombiner;
-import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.GrayLogRankDifferentiator;
-import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankDifferentiator;
+import ca.joeltherrien.randomforest.responses.competingrisk.splitfinder.GrayLogRankSplitFinder;
+import ca.joeltherrien.randomforest.responses.competingrisk.splitfinder.LogRankSplitFinder;
import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
-import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
-import ca.joeltherrien.randomforest.tree.GroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceSplitFinder;
+import ca.joeltherrien.randomforest.tree.SplitFinder;
import ca.joeltherrien.randomforest.tree.ResponseCombiner;
import ca.joeltherrien.randomforest.utils.DataUtils;
import ca.joeltherrien.randomforest.utils.Utils;
@@ -77,31 +77,31 @@ public class Settings {
);
}
- private static Map<String, Function<ObjectNode, GroupDifferentiator>> GROUP_DIFFERENTIATOR_MAP = new HashMap<>();
- public static Function<ObjectNode, GroupDifferentiator> getGroupDifferentiatorConstructor(final String name){
- return GROUP_DIFFERENTIATOR_MAP.get(name.toLowerCase());
+ private static Map<String, Function<ObjectNode, SplitFinder>> SPLIT_FINDER_MAP = new HashMap<>();
+ public static Function<ObjectNode, SplitFinder> getSplitFinderConstructor(final String name){
+ return SPLIT_FINDER_MAP.get(name.toLowerCase());
}
- public static void registerGroupDifferentiatorConstructor(final String name, final Function<ObjectNode, GroupDifferentiator> groupDifferentiatorConstructor){
- GROUP_DIFFERENTIATOR_MAP.put(name.toLowerCase(), groupDifferentiatorConstructor);
+ public static void registerSplitFinderConstructor(final String name, final Function<ObjectNode, SplitFinder> splitFinderConstructor){
+ SPLIT_FINDER_MAP.put(name.toLowerCase(), splitFinderConstructor);
}
static{
- registerGroupDifferentiatorConstructor("WeightedVarianceGroupDifferentiator",
- (node) -> new WeightedVarianceGroupDifferentiator()
+ registerSplitFinderConstructor("WeightedVarianceSplitFinder",
+ (node) -> new WeightedVarianceSplitFinder()
);
- registerGroupDifferentiatorConstructor("GrayLogRankDifferentiator",
+ registerSplitFinderConstructor("GrayLogRankSplitFinder",
(objectNode) -> {
final int[] eventsOfFocusArray = Utils.jsonToIntArray(objectNode.get("eventsOfFocus"));
final int[] eventArray = Utils.jsonToIntArray(objectNode.get("events"));
- return new GrayLogRankDifferentiator(eventsOfFocusArray, eventArray);
+ return new GrayLogRankSplitFinder(eventsOfFocusArray, eventArray);
}
);
- registerGroupDifferentiatorConstructor("LogRankDifferentiator",
+ registerSplitFinderConstructor("LogRankSplitFinder",
(objectNode) -> {
final int[] eventsOfFocusArray = Utils.jsonToIntArray(objectNode.get("eventsOfFocus"));
final int[] eventArray = Utils.jsonToIntArray(objectNode.get("events"));
- return new LogRankDifferentiator(eventsOfFocusArray, eventArray);
+ return new LogRankSplitFinder(eventsOfFocusArray, eventArray);
}
);
}
@@ -153,7 +153,7 @@ public class Settings {
private boolean checkNodePurity = false;
private ObjectNode responseCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
- private ObjectNode groupDifferentiatorSettings = new ObjectNode(JsonNodeFactory.instance);
+ private ObjectNode splitFinderSettings = new ObjectNode(JsonNodeFactory.instance);
private ObjectNode treeCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
private List<CovariateSettings> covariateSettings = new ArrayList<>();
@@ -194,10 +194,10 @@ public class Settings {
}
@JsonIgnore
- public GroupDifferentiator getGroupDifferentiator(){
- final String type = groupDifferentiatorSettings.get("type").asText();
+ public SplitFinder getSplitFinder(){
+ final String type = splitFinderSettings.get("type").asText();
- return getGroupDifferentiatorConstructor(type).apply(groupDifferentiatorSettings);
+ return getSplitFinderConstructor(type).apply(splitFinderSettings);
}
@JsonIgnore
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/CompetingRiskSplitFinder.java
similarity index 92%
rename from src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/CompetingRiskSplitFinder.java
index aef9b4c..b2cddb8 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/CompetingRiskGroupDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/CompetingRiskSplitFinder.java
@@ -14,13 +14,13 @@
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
-package ca.joeltherrien.randomforest.responses.competingrisk.differentiator;
+package ca.joeltherrien.randomforest.responses.competingrisk.splitfinder;
import ca.joeltherrien.randomforest.Row;
import ca.joeltherrien.randomforest.covariates.Covariate;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets;
-import ca.joeltherrien.randomforest.tree.GroupDifferentiator;
+import ca.joeltherrien.randomforest.tree.SplitFinder;
import ca.joeltherrien.randomforest.tree.Split;
import ca.joeltherrien.randomforest.tree.SplitAndScore;
import lombok.AllArgsConstructor;
@@ -35,24 +35,24 @@ import java.util.stream.Collectors;
* modifies the abstract method.
*
*/
-public abstract class CompetingRiskGroupDifferentiator<Y extends CompetingRiskResponse> implements GroupDifferentiator<Y> {
+public abstract class CompetingRiskSplitFinder<Y extends CompetingRiskResponse> implements SplitFinder<Y> {
abstract protected CompetingRiskSets<Y> createCompetingRiskSets(List<Y> leftHand, List<Y> rightHand);
abstract protected Double getScore(final CompetingRiskSets<Y> competingRiskSets);
@Override
- public SplitAndScore<Y, ?> differentiate(Iterator<Split<Y, ?>> splitIterator) {
+ public SplitAndScore<Y, ?> findBestSplit(Iterator<Split<Y, ?>> splitIterator) {
if(splitIterator instanceof Covariate.SplitRuleUpdater){
- return differentiateWithSplitUpdater((Covariate.SplitRuleUpdater) splitIterator);
+ return findBestSplitWithSplitUpdater((Covariate.SplitRuleUpdater) splitIterator);
}
else{
- return differentiateWithBasicIterator(splitIterator);
+ return findBestSplitWithBasicIterator(splitIterator);
}
}
- private SplitAndScore<Y, ?> differentiateWithBasicIterator(Iterator<Split<Y, ?>> splitIterator){
+ private SplitAndScore<Y, ?> findBestSplitWithBasicIterator(Iterator<Split<Y, ?>> splitIterator){
Double bestScore = null;
Split<Y, ?> bestSplit = null;
@@ -83,7 +83,7 @@ public abstract class CompetingRiskGroupDifferentiator<Y extends CompetingRiskRe
return new SplitAndScore<>(bestSplit, bestScore);
}
- private SplitAndScore<Y, ?> differentiateWithSplitUpdater(Covariate.SplitRuleUpdater<Y, ?> splitRuleUpdater) {
+ private SplitAndScore<Y, ?> findBestSplitWithSplitUpdater(Covariate.SplitRuleUpdater<Y, ?> splitRuleUpdater) {
final List<Y> leftInitialSplit = splitRuleUpdater.currentSplit().getLeftHand()
.stream().map(Row::getResponse).collect(Collectors.toList());
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/GrayLogRankSplitFinder.java
similarity index 91%
rename from src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/GrayLogRankSplitFinder.java
index 420ad15..b6eed13 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/GrayLogRankDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/GrayLogRankSplitFinder.java
@@ -14,7 +14,7 @@
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
-package ca.joeltherrien.randomforest.responses.competingrisk.differentiator;
+package ca.joeltherrien.randomforest.responses.competingrisk.splitfinder;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponseWithCensorTime;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets;
@@ -27,12 +27,12 @@ import java.util.List;
* See page 761 of Random survival forests for competing risks by Ishwaran et al.
*
*/
-public class GrayLogRankDifferentiator extends CompetingRiskGroupDifferentiator<CompetingRiskResponseWithCensorTime> {
+public class GrayLogRankSplitFinder extends CompetingRiskSplitFinder<CompetingRiskResponseWithCensorTime> {
private final int[] eventsOfFocus;
private final int[] events;
- public GrayLogRankDifferentiator(int[] eventsOfFocus, int[] events){
+ public GrayLogRankSplitFinder(int[] eventsOfFocus, int[] events){
this.eventsOfFocus = eventsOfFocus;
this.events = events;
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/LogRankSplitFinder.java
similarity index 91%
rename from src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/LogRankSplitFinder.java
index d528de3..c31bb84 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/differentiator/LogRankDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/competingrisk/splitfinder/LogRankSplitFinder.java
@@ -14,7 +14,7 @@
* along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
-package ca.joeltherrien.randomforest.responses.competingrisk.differentiator;
+package ca.joeltherrien.randomforest.responses.competingrisk.splitfinder;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskSets;
@@ -27,12 +27,12 @@ import java.util.List;
* See page 761 of Random survival forests for competing risks by Ishwaran et al.
*
*/
-public class LogRankDifferentiator extends CompetingRiskGroupDifferentiator<CompetingRiskResponse> {
+public class LogRankSplitFinder extends CompetingRiskSplitFinder<CompetingRiskResponse> {
private final int[] eventsOfFocus;
private final int[] events;
- public LogRankDifferentiator(int[] eventsOfFocus, int[] events){
+ public LogRankSplitFinder(int[] eventsOfFocus, int[] events){
this.eventsOfFocus = eventsOfFocus;
this.events = events;
diff --git a/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceSplitFinder.java
similarity index 91%
rename from src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceSplitFinder.java
index a16f403..9fb4d43 100644
--- a/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceGroupDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/responses/regression/WeightedVarianceSplitFinder.java
@@ -18,7 +18,7 @@ package ca.joeltherrien.randomforest.responses.regression;
import ca.joeltherrien.randomforest.Row;
import ca.joeltherrien.randomforest.covariates.Covariate;
-import ca.joeltherrien.randomforest.tree.GroupDifferentiator;
+import ca.joeltherrien.randomforest.tree.SplitFinder;
import ca.joeltherrien.randomforest.tree.Split;
import ca.joeltherrien.randomforest.tree.SplitAndScore;
@@ -26,7 +26,7 @@ import java.util.Iterator;
import java.util.List;
import java.util.stream.Collectors;
-public class WeightedVarianceGroupDifferentiator implements GroupDifferentiator<Double> {
+public class WeightedVarianceSplitFinder implements SplitFinder<Double> {
private Double getScore(Set leftHand, Set rightHand) {
@@ -44,17 +44,17 @@ public class WeightedVarianceGroupDifferentiator implements GroupDifferentiator<
}
@Override
- public SplitAndScore<Double, ?> differentiate(Iterator<Split<Double, ?>> splitIterator) {
+ public SplitAndScore<Double, ?> findBestSplit(Iterator<Split<Double, ?>> splitIterator) {
if(splitIterator instanceof Covariate.SplitRuleUpdater){
- return differentiateWithSplitUpdater((Covariate.SplitRuleUpdater) splitIterator);
+ return findBestSplitWithSplitUpdater((Covariate.SplitRuleUpdater) splitIterator);
}
else{
- return differentiateWithBasicIterator(splitIterator);
+ return findBestSplitWithBasicIterator(splitIterator);
}
}
- private SplitAndScore<Double, ?> differentiateWithBasicIterator(Iterator<Split<Double, ?>> splitIterator){
+ private SplitAndScore<Double, ?> findBestSplitWithBasicIterator(Iterator<Split<Double, ?>> splitIterator){
Double bestScore = null;
Split<Double, ?> bestSplit = null;
@@ -86,7 +86,7 @@ public class WeightedVarianceGroupDifferentiator implements GroupDifferentiator<
return new SplitAndScore<>(bestSplit, bestScore);
}
- private SplitAndScore<Double, ?> differentiateWithSplitUpdater(Covariate.SplitRuleUpdater<Double, ?> splitRuleUpdater) {
+ private SplitAndScore<Double, ?> findBestSplitWithSplitUpdater(Covariate.SplitRuleUpdater<Double, ?> splitRuleUpdater) {
final List<Double> leftInitialSplit = splitRuleUpdater.currentSplit().getLeftHand()
.stream().map(Row::getResponse).collect(Collectors.toList());
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/tree/SimpleSplitFinder.java
similarity index 93%
rename from src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/tree/SimpleSplitFinder.java
index 2cacec7..7fabe4b 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/SimpleGroupDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/SimpleSplitFinder.java
@@ -22,10 +22,10 @@ import java.util.Iterator;
import java.util.List;
import java.util.stream.Collectors;
-public abstract class SimpleGroupDifferentiator<Y> implements GroupDifferentiator<Y> {
+public abstract class SimpleSplitFinder<Y> implements SplitFinder<Y> {
@Override
- public SplitAndScore<Y, ?> differentiate(Iterator<Split<Y, ?>> splitIterator) {
+ public SplitAndScore<Y, ?> findBestSplit(Iterator<Split<Y, ?>> splitIterator) {
Double bestScore = null;
Split<Y, ?> bestSplit = null;
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java b/src/main/java/ca/joeltherrien/randomforest/tree/SplitFinder.java
similarity index 73%
rename from src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java
rename to src/main/java/ca/joeltherrien/randomforest/tree/SplitFinder.java
index 8d72efb..3f09dd5 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/GroupDifferentiator.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/SplitFinder.java
@@ -21,14 +21,14 @@ import java.util.Iterator;
/**
* When choosing an optimal node to split on, we choose the split that maximizes the difference between the two groups.
- * The GroupDifferentiator has one method that cycles through an iterator of Splits (FYI; check if the iterator is an
+ * The SplitFinder has one method that cycles through an iterator of Splits (FYI; check if the iterator is an
* instance of Covariate.SplitRuleUpdater; in which case you get access to the rows that change between splits)
*
- * If you want to implement a very trivial GroupDifferentiator that just takes two Lists as arguments, try extending
- * SimpleGroupDifferentiator.
+ * If you want to implement a very trivial SplitFinder that just takes two Lists as arguments, try extending
+ * SimpleSplitFinder.
*/
-public interface GroupDifferentiator<Y> extends Serializable {
+public interface SplitFinder<Y> extends Serializable {
- SplitAndScore<Y, ?> differentiate(Iterator<Split<Y, ?>> splitIterator);
+ SplitAndScore<Y, ?> findBestSplit(Iterator<Split<Y, ?>> splitIterator);
}
diff --git a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
index a633664..6e016c8 100644
--- a/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
+++ b/src/main/java/ca/joeltherrien/randomforest/tree/TreeTrainer.java
@@ -31,7 +31,7 @@ import java.util.stream.Collectors;
public class TreeTrainer<Y, O> {
private final ResponseCombiner<Y, O> responseCombiner;
- private final GroupDifferentiator<Y> groupDifferentiator;
+ private final SplitFinder<Y> splitFinder;
/**
* The number of splits to perform on each covariate. A value of 0 means all possible splits are tried.
@@ -58,7 +58,7 @@ public class TreeTrainer<Y, O> {
this.checkNodePurity = settings.isCheckNodePurity();
this.responseCombiner = settings.getResponseCombiner();
- this.groupDifferentiator = settings.getGroupDifferentiator();
+ this.splitFinder = settings.getSplitFinder();
this.covariates = covariates;
}
@@ -160,7 +160,7 @@ public class TreeTrainer<Y, O> {
private Split<Y, ?> findBestSplitRule(List<Row<Y>> data, List<Covariate> covariatesToTry, Random random){
SplitAndScore<Y, ?> bestSplitAndScore = null;
- final GroupDifferentiator noGenericDifferentiator = groupDifferentiator; // cause Java generics suck
+ final SplitFinder noGenericSplitFinder = splitFinder; // cause Java generics are sometimes too frustrating
for(final Covariate covariate : covariatesToTry) {
final Iterator<Split> iterator = covariate.generateSplitRuleUpdater(data, this.numberOfSplits, random);
@@ -170,7 +170,7 @@ public class TreeTrainer<Y, O> {
continue;
}
- final SplitAndScore<Y, ?> candidateSplitAndScore = noGenericDifferentiator.differentiate(iterator);
+ final SplitAndScore<Y, ?> candidateSplitAndScore = noGenericSplitFinder.findBestSplit(iterator);
if(candidateSplitAndScore != null && (bestSplitAndScore == null ||
candidateSplitAndScore.getScore() > bestSplitAndScore.getScore())) {
diff --git a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
index 58dd3e7..7ae2dea 100644
--- a/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
+++ b/src/test/java/ca/joeltherrien/randomforest/TestSavingLoading.java
@@ -44,12 +44,12 @@ public class TestSavingLoading {
* @return
*/
public Settings getSettings(){
- final ObjectNode groupDifferentiatorSettings = new ObjectNode(JsonNodeFactory.instance);
- groupDifferentiatorSettings.set("type", new TextNode("LogRankDifferentiator"));
- groupDifferentiatorSettings.set("eventsOfFocus",
+ final ObjectNode splitRuleSettings = new ObjectNode(JsonNodeFactory.instance);
+ splitRuleSettings.set("type", new TextNode("LogRankSplitFinder"));
+ splitRuleSettings.set("eventsOfFocus",
new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1)))
);
- groupDifferentiatorSettings.set("events",
+ splitRuleSettings.set("events",
new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
);
@@ -85,7 +85,7 @@ public class TestSavingLoading {
.validationDataLocation("src/test/resources/wihs.csv")
.responseCombinerSettings(responseCombinerSettings)
.treeCombinerSettings(treeCombinerSettings)
- .groupDifferentiatorSettings(groupDifferentiatorSettings)
+ .splitFinderSettings(splitRuleSettings)
.yVarSettings(yVarSettings)
.maxNodeDepth(100000)
// TODO fill in these settings
diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
index 9ba04d7..1f78096 100644
--- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
+++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestCompetingRisk.java
@@ -53,12 +53,12 @@ public class TestCompetingRisk {
* @return
*/
public Settings getSettings(){
- final ObjectNode groupDifferentiatorSettings = new ObjectNode(JsonNodeFactory.instance);
- groupDifferentiatorSettings.set("type", new TextNode("LogRankDifferentiator"));
- groupDifferentiatorSettings.set("eventsOfFocus",
+ final ObjectNode splitFinderSettings = new ObjectNode(JsonNodeFactory.instance);
+ splitFinderSettings.set("type", new TextNode("LogRankSplitFinder"));
+ splitFinderSettings.set("eventsOfFocus",
new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1)))
);
- groupDifferentiatorSettings.set("events",
+ splitFinderSettings.set("events",
new ArrayNode(JsonNodeFactory.instance, Utils.easyList(new IntNode(1), new IntNode(2)))
);
@@ -93,7 +93,7 @@ public class TestCompetingRisk {
.trainingDataLocation("src/test/resources/wihs.csv")
.responseCombinerSettings(responseCombinerSettings)
.treeCombinerSettings(treeCombinerSettings)
- .groupDifferentiatorSettings(groupDifferentiatorSettings)
+ .splitFinderSettings(splitFinderSettings)
.yVarSettings(yVarSettings)
.maxNodeDepth(100000)
// TODO fill in these settings
@@ -222,7 +222,7 @@ public class TestCompetingRisk {
}
@Test
- public void testLogRankSingleGroupDifferentiatorTwoBooleans() throws IOException {
+ public void testLogRankSplitFinderTwoBooleans() throws IOException {
final Settings settings = getSettings();
settings.setCovariateSettings(Utils.easyList(
new BooleanCovariateSettings("idu"),
@@ -337,7 +337,7 @@ public class TestCompetingRisk {
}
@Test
- public void testLogRankSingleGroupDifferentiatorAllCovariates() throws IOException {
+ public void testLogRankSplitFinderAllCovariates() throws IOException {
final Settings settings = getSettings();
settings.setNtree(300); // results are too variable at 100
diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankDifferentiator.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinder.java
similarity index 91%
rename from src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankDifferentiator.java
rename to src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinder.java
index 6a600dd..259410b 100644
--- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankDifferentiator.java
+++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinder.java
@@ -21,7 +21,7 @@ import ca.joeltherrien.randomforest.Settings;
import ca.joeltherrien.randomforest.covariates.Covariate;
import ca.joeltherrien.randomforest.covariates.settings.NumericCovariateSettings;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
-import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankDifferentiator;
+import ca.joeltherrien.randomforest.responses.competingrisk.splitfinder.LogRankSplitFinder;
import ca.joeltherrien.randomforest.tree.Split;
import ca.joeltherrien.randomforest.utils.DataUtils;
import ca.joeltherrien.randomforest.utils.SingletonIterator;
@@ -39,7 +39,7 @@ import java.util.List;
import static org.junit.jupiter.api.Assertions.assertTrue;
-public class TestLogRankDifferentiator {
+public class TestLogRankSplitFinder {
private Iterator<Split<CompetingRiskResponse, ?>> turnIntoSplitIterator(List<Row<CompetingRiskResponse>> leftList,
List<Row<CompetingRiskResponse>> rightList){
@@ -70,14 +70,14 @@ public class TestLogRankDifferentiator {
@Test
public void testSplitRule() throws IOException {
- final LogRankDifferentiator groupDifferentiator = new LogRankDifferentiator(new int[]{1,2}, new int[]{1,2});
+ final LogRankSplitFinder splitFinder = new LogRankSplitFinder(new int[]{1,2}, new int[]{1,2});
final List<Row<CompetingRiskResponse>> data = loadData("src/test/resources/test_split_data.csv").getRows();
final List<Row<CompetingRiskResponse>> group1Bad = data.subList(0, 196);
final List<Row<CompetingRiskResponse>> group2Bad = data.subList(196, data.size());
- final double scoreBad = groupDifferentiator.differentiate(turnIntoSplitIterator(group1Bad, group2Bad)).getScore();
+ final double scoreBad = splitFinder.findBestSplit(turnIntoSplitIterator(group1Bad, group2Bad)).getScore();
// expected results calculated manually using survival::survdiff in R; see issue #10 in Gitea
closeEnough(9.413002, scoreBad, 0.00001);
diff --git a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinderSingleEvent.java
similarity index 80%
rename from src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java
rename to src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinderSingleEvent.java
index 8b0693f..205500f 100644
--- a/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSingleGroupDifferentiator.java
+++ b/src/test/java/ca/joeltherrien/randomforest/competingrisk/TestLogRankSplitFinderSingleEvent.java
@@ -18,8 +18,8 @@ package ca.joeltherrien.randomforest.competingrisk;
import ca.joeltherrien.randomforest.Row;
import ca.joeltherrien.randomforest.responses.competingrisk.CompetingRiskResponse;
-import ca.joeltherrien.randomforest.responses.competingrisk.differentiator.LogRankDifferentiator;
-import ca.joeltherrien.randomforest.tree.GroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.competingrisk.splitfinder.LogRankSplitFinder;
+import ca.joeltherrien.randomforest.tree.SplitFinder;
import ca.joeltherrien.randomforest.tree.Split;
import ca.joeltherrien.randomforest.utils.SingletonIterator;
import org.junit.jupiter.api.Test;
@@ -33,13 +33,13 @@ import java.util.List;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertTrue;
-public class TestLogRankSingleGroupDifferentiator {
+public class TestLogRankSplitFinderSingleEvent {
- private double getScore(final GroupDifferentiator<CompetingRiskResponse> groupDifferentiator, List<Row<CompetingRiskResponse>> left, List<Row<CompetingRiskResponse>> right){
+ private double getScore(final SplitFinder<CompetingRiskResponse> splitFinder, List<Row<CompetingRiskResponse>> left, List<Row<CompetingRiskResponse>> right){
final Iterator<Split<CompetingRiskResponse, ?>> iterator = new SingletonIterator<>(
new Split<>(null, left, right, Collections.emptyList()));
- return groupDifferentiator.differentiate(iterator).getScore();
+ return splitFinder.findBestSplit(iterator).getScore();
}
@@ -81,9 +81,9 @@ public class TestLogRankSingleGroupDifferentiator {
final List<Row<CompetingRiskResponse>> data1 = generateData1();
final List<Row<CompetingRiskResponse>> data2 = generateData2();
- final LogRankDifferentiator differentiator = new LogRankDifferentiator(new int[]{1}, new int[]{1});
+ final LogRankSplitFinder splitFinder = new LogRankSplitFinder(new int[]{1}, new int[]{1});
- final double score = getScore(differentiator, data1, data2);
+ final double score = getScore(splitFinder, data1, data2);
final double margin = 0.000001;
// Tested using 855 method
@@ -94,21 +94,21 @@ public class TestLogRankSingleGroupDifferentiator {
@Test
public void testCorrectSplit() throws IOException {
- final LogRankDifferentiator groupDifferentiator =
- new LogRankDifferentiator(new int[]{1}, new int[]{1,2});
+ final LogRankSplitFinder splitFinder =
+ new LogRankSplitFinder(new int[]{1}, new int[]{1,2});
- final List<Row<CompetingRiskResponse>> data = TestLogRankDifferentiator.
+ final List<Row<CompetingRiskResponse>> data = TestLogRankSplitFinder.
loadData("src/test/resources/test_single_split.csv").getRows();
final List<Row<CompetingRiskResponse>> group1Good = data.subList(0, 221);
final List<Row<CompetingRiskResponse>> group2Good = data.subList(221, data.size());
- final double scoreGood = getScore(groupDifferentiator, group1Good, group2Good);
+ final double scoreGood = getScore(splitFinder, group1Good, group2Good);
final List<Row<CompetingRiskResponse>> group1Bad = data.subList(0, 222);
final List<Row<CompetingRiskResponse>> group2Bad = data.subList(222, data.size());
- final double scoreBad = getScore(groupDifferentiator, group1Bad, group2Bad);
+ final double scoreBad = getScore(splitFinder, group1Bad, group2Bad);
// Apparently not all groups are unique when splitting
assertEquals(scoreGood, scoreBad);
diff --git a/src/test/java/ca/joeltherrien/randomforest/nas/TestNAs.java b/src/test/java/ca/joeltherrien/randomforest/nas/TestNAs.java
index d748f1e..cb9a116 100644
--- a/src/test/java/ca/joeltherrien/randomforest/nas/TestNAs.java
+++ b/src/test/java/ca/joeltherrien/randomforest/nas/TestNAs.java
@@ -4,7 +4,7 @@ import ca.joeltherrien.randomforest.Row;
import ca.joeltherrien.randomforest.covariates.Covariate;
import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate;
import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
-import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceSplitFinder;
import ca.joeltherrien.randomforest.tree.TreeTrainer;
import ca.joeltherrien.randomforest.utils.Utils;
import org.junit.jupiter.api.Test;
@@ -47,7 +47,7 @@ public class TestNAs {
.numberOfSplits(0)
.nodeSize(1)
.maxNodeDepth(1000)
- .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
+ .splitFinder(new WeightedVarianceSplitFinder())
.responseCombiner(new MeanResponseCombiner())
.build();
diff --git a/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java b/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java
index d1d0a41..acac42f 100644
--- a/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java
+++ b/src/test/java/ca/joeltherrien/randomforest/settings/TestPersistence.java
@@ -35,8 +35,8 @@ public class TestPersistence {
@Test
public void testSaving() throws IOException {
- final ObjectNode groupDifferentiatorSettings = new ObjectNode(JsonNodeFactory.instance);
- groupDifferentiatorSettings.set("type", new TextNode("WeightedVarianceGroupDifferentiator"));
+ final ObjectNode splitFinderSettings = new ObjectNode(JsonNodeFactory.instance);
+ splitFinderSettings.set("type", new TextNode("WeightedVarianceSplitFinder"));
final ObjectNode responseCombinerSettings = new ObjectNode(JsonNodeFactory.instance);
responseCombinerSettings.set("type", new TextNode("MeanResponseCombiner"));
@@ -59,7 +59,7 @@ public class TestPersistence {
.validationDataLocation("validation_data.csv")
.responseCombinerSettings(responseCombinerSettings)
.treeCombinerSettings(treeCombinerSettings)
- .groupDifferentiatorSettings(groupDifferentiatorSettings)
+ .splitFinderSettings(splitFinderSettings)
.yVarSettings(yVarSettings)
.maxNodeDepth(100000)
.mtry(2)
diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java
index 8579e0e..b27045e 100644
--- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java
+++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainForest.java
@@ -20,7 +20,7 @@ import ca.joeltherrien.randomforest.*;
import ca.joeltherrien.randomforest.covariates.Covariate;
import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate;
import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
-import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceSplitFinder;
import ca.joeltherrien.randomforest.tree.ForestTrainer;
import ca.joeltherrien.randomforest.tree.TreeTrainer;
@@ -72,7 +72,7 @@ public class TrainForest {
.nodeSize(5)
.mtry(4)
.maxNodeDepth(100000000)
- .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
+ .splitFinder(new WeightedVarianceSplitFinder())
.responseCombiner(new MeanResponseCombiner())
.build();
diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java
index 1527d4a..8e1e361 100644
--- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java
+++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTree.java
@@ -22,7 +22,7 @@ import ca.joeltherrien.randomforest.CovariateRow;
import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate;
import ca.joeltherrien.randomforest.Row;
import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
-import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceSplitFinder;
import ca.joeltherrien.randomforest.tree.Node;
import ca.joeltherrien.randomforest.tree.TreeTrainer;
import ca.joeltherrien.randomforest.utils.Utils;
@@ -66,7 +66,7 @@ public class TrainSingleTree {
final List<Covariate> covariateNames = Utils.easyList(x1Covariate, x2Covariate);
final TreeTrainer<Double, Double> treeTrainer = TreeTrainer.<Double, Double>builder()
- .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
+ .splitFinder(new WeightedVarianceSplitFinder())
.covariates(covariateNames)
.responseCombiner(new MeanResponseCombiner())
.maxNodeDepth(30)
diff --git a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java
index 7313d22..1d2b404 100644
--- a/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java
+++ b/src/test/java/ca/joeltherrien/randomforest/workshop/TrainSingleTreeFactor.java
@@ -22,7 +22,7 @@ import ca.joeltherrien.randomforest.covariates.Covariate;
import ca.joeltherrien.randomforest.covariates.factor.FactorCovariate;
import ca.joeltherrien.randomforest.covariates.numeric.NumericCovariate;
import ca.joeltherrien.randomforest.responses.regression.MeanResponseCombiner;
-import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceGroupDifferentiator;
+import ca.joeltherrien.randomforest.responses.regression.WeightedVarianceSplitFinder;
import ca.joeltherrien.randomforest.tree.Node;
import ca.joeltherrien.randomforest.tree.TreeTrainer;
import ca.joeltherrien.randomforest.utils.Utils;
@@ -86,7 +86,7 @@ public class TrainSingleTreeFactor {
final List<Covariate> covariateNames = Utils.easyList(x1Covariate, x2Covariate);
final TreeTrainer<Double, Double> treeTrainer = TreeTrainer.<Double, Double>builder()
- .groupDifferentiator(new WeightedVarianceGroupDifferentiator())
+ .splitFinder(new WeightedVarianceSplitFinder())
.responseCombiner(new MeanResponseCombiner())
.covariates(covariateNames)
.maxNodeDepth(30)