Converting close to delete() to ensure we drop the dbs when using MapDB.

datumbox · Dec 22, 2016 · 2e387cf · 2e387cf
1 parent 7b8bea5
commit 2e387cf
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Showing 4 changed files with 4 additions and 4 deletions.
diff --git a/...ox-framework-applications/src/main/java/com/datumbox/framework/applications/nlp/CETR.java b/...ox-framework-applications/src/main/java/com/datumbox/framework/applications/nlp/CETR.java
@@ -256,7 +256,7 @@ private void performClustering(Dataframe dataset, int numberOfClusters) {
 
         instance.fit(dataset);
         instance.predict(dataset);
-        instance.close();
+        instance.delete();
     }
 
     private List<Double> calculateTTRlist(List<String> rows) {

diff --git a/...x/framework/core/machinelearning/common/abstracts/algorithms/AbstractBoostingBagging.java b/...x/framework/core/machinelearning/common/abstracts/algorithms/AbstractBoostingBagging.java
@@ -255,7 +255,7 @@ protected void _fit(Dataframe trainingData) {
 
             Status status = updateObservationAndClassifierWeights(trainingData, observationWeights);
             if(status == Status.IGNORE) {
-                mlclassifier.close();
+                mlclassifier.delete();
             }
             else {
                 bundle.put(DB_INDICATOR + i, mlclassifier);

diff --git a/...com/datumbox/framework/core/machinelearning/modelselection/validators/KFoldValidator.java b/...com/datumbox/framework/core/machinelearning/modelselection/validators/KFoldValidator.java
@@ -130,7 +130,7 @@ public VM validate(Dataframe dataset, TrainingParameters trainingParameters) {
             //add the validationMetrics in the list
             validationMetricsList.add(entrySample);
         }
-        modeler.close();
+        modeler.delete();
 
         VM avgValidationMetrics = ValidationMetrics.newInstance(vmClass, validationMetricsList);
 

diff --git a/.../main/java/com/datumbox/framework/core/machinelearning/regression/StepwiseRegression.java b/.../main/java/com/datumbox/framework/core/machinelearning/regression/StepwiseRegression.java
@@ -273,7 +273,7 @@ private Map<Object, Double> runRegression(Dataframe trainingData) {
 
         Map<Object, Double> pvalues = ((StepwiseCompatible)mlregressor).getFeaturePvalues();
 
-        mlregressor.close();
+        mlregressor.delete();
 
         return pvalues;
     }