IGNITE-10380: Drop Multi-label Classification for

Logistic Regression and SVM This closes #5559
apache · Dec 5, 2018 · 098caf4 · 098caf4
1 parent 46ff268
commit 098caf4
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Showing 34 changed files with 64 additions and 1,599 deletions.
diff --git a/...ite/examples/ml/regression/logistic/bagged/BaggedLogisticRegressionSGDTrainerExample.java b/...ite/examples/ml/regression/logistic/bagged/BaggedLogisticRegressionSGDTrainerExample.java
@@ -30,7 +30,7 @@
 import org.apache.ignite.ml.nn.UpdatesStrategy;
 import org.apache.ignite.ml.optimization.updatecalculators.SimpleGDParameterUpdate;
 import org.apache.ignite.ml.optimization.updatecalculators.SimpleGDUpdateCalculator;
-import org.apache.ignite.ml.regressions.logistic.binomial.LogisticRegressionSGDTrainer;
+import org.apache.ignite.ml.regressions.logistic.LogisticRegressionSGDTrainer;
 import org.apache.ignite.ml.selection.cv.CrossValidation;
 import org.apache.ignite.ml.selection.scoring.metric.Accuracy;
 import org.apache.ignite.ml.trainers.DatasetTrainer;

diff --git a/...he/ignite/examples/ml/regression/logistic/binary/LogisticRegressionSGDTrainerExample.java b/...he/ignite/examples/ml/regression/logistic/binary/LogisticRegressionSGDTrainerExample.java
@@ -31,8 +31,8 @@
 import org.apache.ignite.ml.nn.UpdatesStrategy;
 import org.apache.ignite.ml.optimization.updatecalculators.SimpleGDParameterUpdate;
 import org.apache.ignite.ml.optimization.updatecalculators.SimpleGDUpdateCalculator;
-import org.apache.ignite.ml.regressions.logistic.binomial.LogisticRegressionModel;
+import org.apache.ignite.ml.regressions.logistic.LogisticRegressionModel;
-import org.apache.ignite.ml.regressions.logistic.binomial.LogisticRegressionSGDTrainer;
+import org.apache.ignite.ml.regressions.logistic.LogisticRegressionSGDTrainer;
 
 /**
  * Run logistic regression model based on <a href="https://en.wikipedia.org/wiki/Stochastic_gradient_descent">

diff --git a/...mples/ml/regression/logistic/multiclass/LogRegressionMultiClassClassificationExample.java b/...mples/ml/regression/logistic/multiclass/LogRegressionMultiClassClassificationExample.java
diff --git a/.../main/java/org/apache/ignite/examples/ml/regression/logistic/multiclass/package-info.java b/.../main/java/org/apache/ignite/examples/ml/regression/logistic/multiclass/package-info.java
diff --git a/...inary/SVMBinaryClassificationExample.java → ...l/svm/SVMBinaryClassificationExample.java b/...inary/SVMBinaryClassificationExample.java → ...l/svm/SVMBinaryClassificationExample.java
@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.ignite.examples.ml.svm.binary;
+package org.apache.ignite.examples.ml.svm;
 
 import java.io.FileNotFoundException;
 import java.util.Arrays;
@@ -28,11 +28,11 @@
 import org.apache.ignite.examples.ml.util.MLSandboxDatasets;
 import org.apache.ignite.examples.ml.util.SandboxMLCache;
 import org.apache.ignite.ml.math.primitives.vector.Vector;
-import org.apache.ignite.ml.svm.SVMLinearBinaryClassificationModel;
+import org.apache.ignite.ml.svm.SVMLinearClassificationModel;
-import org.apache.ignite.ml.svm.SVMLinearBinaryClassificationTrainer;
+import org.apache.ignite.ml.svm.SVMLinearClassificationTrainer;
 
 /**
- * Run SVM binary-class classification model ({@link SVMLinearBinaryClassificationModel}) over distributed dataset.
+ * Run SVM binary-class classification model ({@link SVMLinearClassificationModel}) over distributed dataset.
  * <p>
  * Code in this example launches Ignite grid and fills the cache with test data points (based on the
  * <a href="https://en.wikipedia.org/wiki/Iris_flower_data_set"></a>Iris dataset</a>).</p>
@@ -57,9 +57,9 @@ public static void main(String[] args) throws FileNotFoundException {
             IgniteCache<Integer, Vector> dataCache = new SandboxMLCache(ignite)
                 .fillCacheWith(MLSandboxDatasets.TWO_CLASSED_IRIS);
 
-            SVMLinearBinaryClassificationTrainer trainer = new SVMLinearBinaryClassificationTrainer();
+            SVMLinearClassificationTrainer trainer = new SVMLinearClassificationTrainer();
 
-            SVMLinearBinaryClassificationModel mdl = trainer.fit(
+            SVMLinearClassificationModel mdl = trainer.fit(
                 ignite,
                 dataCache,
                 (k, v) -> v.copyOfRange(1, v.size()),

diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/svm/binary/package-info.java b/examples/src/main/java/org/apache/ignite/examples/ml/svm/binary/package-info.java