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From sboi...@apache.org
Subject [05/28] ignite git commit: IGNITE-9910: [ML] Move the static copy-pasted datasets from examples to special Util class
Date Tue, 30 Oct 2018 06:08:56 GMT
http://git-wip-us.apache.org/repos/asf/ignite/blob/370cd3e1/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestRegressionExample.java
----------------------------------------------------------------------
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestRegressionExample.java b/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestRegressionExample.java
index 9b4aece..3bf2c8e 100644
--- a/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestRegressionExample.java
+++ b/examples/src/main/java/org/apache/ignite/examples/ml/tree/randomforest/RandomForestRegressionExample.java
@@ -17,7 +17,7 @@
 
 package org.apache.ignite.examples.ml.tree.randomforest;
 
-import java.util.Arrays;
+import java.io.FileNotFoundException;
 import java.util.concurrent.atomic.AtomicInteger;
 import java.util.stream.Collectors;
 import java.util.stream.IntStream;
@@ -27,14 +27,15 @@ import org.apache.ignite.IgniteCache;
 import org.apache.ignite.Ignition;
 import org.apache.ignite.cache.query.QueryCursor;
 import org.apache.ignite.cache.query.ScanQuery;
-import org.apache.ignite.examples.ml.util.TestCache;
+import org.apache.ignite.examples.ml.util.MLSandboxDatasets;
+import org.apache.ignite.examples.ml.util.SandboxMLCache;
 import org.apache.ignite.ml.composition.ModelsComposition;
 import org.apache.ignite.ml.dataset.feature.FeatureMeta;
 import org.apache.ignite.ml.environment.LearningEnvironment;
 import org.apache.ignite.ml.environment.logging.ConsoleLogger;
 import org.apache.ignite.ml.environment.logging.MLLogger;
 import org.apache.ignite.ml.environment.parallelism.ParallelismStrategy;
-import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
+import org.apache.ignite.ml.math.primitives.vector.Vector;
 import org.apache.ignite.ml.tree.randomforest.RandomForestRegressionTrainer;
 import org.apache.ignite.ml.tree.randomforest.data.FeaturesCountSelectionStrategies;
 
@@ -58,18 +59,19 @@ public class RandomForestRegressionExample {
     /**
      * Run example.
      */
-    public static void main(String[] args) throws InterruptedException {
+    public static void main(String[] args) throws FileNotFoundException {
         System.out.println();
         System.out.println(">>> Random Forest regression algorithm over cached dataset usage example started.");
         // Start ignite grid.
         try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
             System.out.println(">>> Ignite grid started.");
 
-            IgniteCache<Integer, double[]> dataCache = new TestCache(ignite).fillCacheWith(data);
+            IgniteCache<Integer, Vector> dataCache = new SandboxMLCache(ignite)
+                .fillCacheWith(MLSandboxDatasets.BOSTON_HOUSE_PRICES);
 
             AtomicInteger idx = new AtomicInteger(0);
             RandomForestRegressionTrainer trainer = new RandomForestRegressionTrainer(
-                IntStream.range(0, data[0].length - 1).mapToObj(
+                IntStream.range(0, dataCache.get(1).size() - 1).mapToObj(
                     x -> new FeatureMeta("", idx.getAndIncrement(), false)).collect(Collectors.toList())
             ).withAmountOfTrees(101)
                 .withFeaturesCountSelectionStrgy(FeaturesCountSelectionStrategies.ONE_THIRD)
@@ -86,24 +88,24 @@ public class RandomForestRegressionExample {
 
             System.out.println(">>> Configured trainer: " + trainer.getClass().getSimpleName());
 
-            ModelsComposition randomForest = trainer.fit(ignite, dataCache,
-                (k, v) -> VectorUtils.of(Arrays.copyOfRange(v, 0, v.length - 1)),
-                (k, v) -> v[v.length - 1]
+            ModelsComposition randomForestMdl = trainer.fit(ignite, dataCache,
+                (k, v) -> v.copyOfRange(1, v.size()),
+                (k, v) -> v.get(0)
             );
 
-            System.out.println(">>> Trained model: " + randomForest.toString(true));
+            System.out.println(">>> Trained model: " + randomForestMdl.toString(true));
 
             double mse = 0.0;
             double mae = 0.0;
             int totalAmount = 0;
 
-            try (QueryCursor<Cache.Entry<Integer, double[]>> observations = dataCache.query(new ScanQuery<>())) {
-                for (Cache.Entry<Integer, double[]> observation : observations) {
-                    double[] val = observation.getValue();
-                    double[] inputs = Arrays.copyOfRange(val, 0, val.length - 1);
-                    double groundTruth = val[val.length - 1];
+            try (QueryCursor<Cache.Entry<Integer, Vector>> observations = dataCache.query(new ScanQuery<>())) {
+                for (Cache.Entry<Integer, Vector> observation : observations) {
+                    Vector val = observation.getValue();
+                    Vector inputs = val.copyOfRange(1, val.size());
+                    double groundTruth = val.get(0);
 
-                    double prediction = randomForest.apply(VectorUtils.of(inputs));
+                    double prediction = randomForestMdl.apply(inputs);
 
                     mse += Math.pow(prediction - groundTruth, 2.0);
                     mae += Math.abs(prediction - groundTruth);
@@ -123,513 +125,4 @@ public class RandomForestRegressionExample {
             }
         }
     }
-
-    /** The Boston housing dataset. */
-    private static final double[][] data = {
-        {0.02731,0.00,7.070,0,0.4690,6.4210,78.90,4.9671,2,242.0,17.80,396.90,9.14,21.60},
-        {0.02729,0.00,7.070,0,0.4690,7.1850,61.10,4.9671,2,242.0,17.80,392.83,4.03,34.70},
-        {0.03237,0.00,2.180,0,0.4580,6.9980,45.80,6.0622,3,222.0,18.70,394.63,2.94,33.40},
-        {0.06905,0.00,2.180,0,0.4580,7.1470,54.20,6.0622,3,222.0,18.70,396.90,5.33,36.20},
-        {0.02985,0.00,2.180,0,0.4580,6.4300,58.70,6.0622,3,222.0,18.70,394.12,5.21,28.70},
-        {0.08829,12.50,7.870,0,0.5240,6.0120,66.60,5.5605,5,311.0,15.20,395.60,12.43,22.90},
-        {0.14455,12.50,7.870,0,0.5240,6.1720,96.10,5.9505,5,311.0,15.20,396.90,19.15,27.10},
-        {0.21124,12.50,7.870,0,0.5240,5.6310,100.00,6.0821,5,311.0,15.20,386.63,29.93,16.50},
-        {0.17004,12.50,7.870,0,0.5240,6.0040,85.90,6.5921,5,311.0,15.20,386.71,17.10,18.90},
-        {0.22489,12.50,7.870,0,0.5240,6.3770,94.30,6.3467,5,311.0,15.20,392.52,20.45,15.00},
-        {0.11747,12.50,7.870,0,0.5240,6.0090,82.90,6.2267,5,311.0,15.20,396.90,13.27,18.90},
-        {0.09378,12.50,7.870,0,0.5240,5.8890,39.00,5.4509,5,311.0,15.20,390.50,15.71,21.70},
-        {0.62976,0.00,8.140,0,0.5380,5.9490,61.80,4.7075,4,307.0,21.00,396.90,8.26,20.40},
-        {0.63796,0.00,8.140,0,0.5380,6.0960,84.50,4.4619,4,307.0,21.00,380.02,10.26,18.20},
-        {0.62739,0.00,8.140,0,0.5380,5.8340,56.50,4.4986,4,307.0,21.00,395.62,8.47,19.90},
-        {1.05393,0.00,8.140,0,0.5380,5.9350,29.30,4.4986,4,307.0,21.00,386.85,6.58,23.10},
-        {0.78420,0.00,8.140,0,0.5380,5.9900,81.70,4.2579,4,307.0,21.00,386.75,14.67,17.50},
-        {0.80271,0.00,8.140,0,0.5380,5.4560,36.60,3.7965,4,307.0,21.00,288.99,11.69,20.20},
-        {0.72580,0.00,8.140,0,0.5380,5.7270,69.50,3.7965,4,307.0,21.00,390.95,11.28,18.20},
-        {1.25179,0.00,8.140,0,0.5380,5.5700,98.10,3.7979,4,307.0,21.00,376.57,21.02,13.60},
-        {0.85204,0.00,8.140,0,0.5380,5.9650,89.20,4.0123,4,307.0,21.00,392.53,13.83,19.60},
-        {1.23247,0.00,8.140,0,0.5380,6.1420,91.70,3.9769,4,307.0,21.00,396.90,18.72,15.20},
-        {0.98843,0.00,8.140,0,0.5380,5.8130,100.00,4.0952,4,307.0,21.00,394.54,19.88,14.50},
-        {0.75026,0.00,8.140,0,0.5380,5.9240,94.10,4.3996,4,307.0,21.00,394.33,16.30,15.60},
-        {0.84054,0.00,8.140,0,0.5380,5.5990,85.70,4.4546,4,307.0,21.00,303.42,16.51,13.90},
-        {0.67191,0.00,8.140,0,0.5380,5.8130,90.30,4.6820,4,307.0,21.00,376.88,14.81,16.60},
-        {0.95577,0.00,8.140,0,0.5380,6.0470,88.80,4.4534,4,307.0,21.00,306.38,17.28,14.80},
-        {0.77299,0.00,8.140,0,0.5380,6.4950,94.40,4.4547,4,307.0,21.00,387.94,12.80,18.40},
-        {1.00245,0.00,8.140,0,0.5380,6.6740,87.30,4.2390,4,307.0,21.00,380.23,11.98,21.00},
-        {1.13081,0.00,8.140,0,0.5380,5.7130,94.10,4.2330,4,307.0,21.00,360.17,22.60,12.70},
-        {1.35472,0.00,8.140,0,0.5380,6.0720,100.00,4.1750,4,307.0,21.00,376.73,13.04,14.50},
-        {1.38799,0.00,8.140,0,0.5380,5.9500,82.00,3.9900,4,307.0,21.00,232.60,27.71,13.20},
-        {1.15172,0.00,8.140,0,0.5380,5.7010,95.00,3.7872,4,307.0,21.00,358.77,18.35,13.10},
-        {1.61282,0.00,8.140,0,0.5380,6.0960,96.90,3.7598,4,307.0,21.00,248.31,20.34,13.50},
-        {0.06417,0.00,5.960,0,0.4990,5.9330,68.20,3.3603,5,279.0,19.20,396.90,9.68,18.90},
-        {0.09744,0.00,5.960,0,0.4990,5.8410,61.40,3.3779,5,279.0,19.20,377.56,11.41,20.00},
-        {0.08014,0.00,5.960,0,0.4990,5.8500,41.50,3.9342,5,279.0,19.20,396.90,8.77,21.00},
-        {0.17505,0.00,5.960,0,0.4990,5.9660,30.20,3.8473,5,279.0,19.20,393.43,10.13,24.70},
-        {0.02763,75.00,2.950,0,0.4280,6.5950,21.80,5.4011,3,252.0,18.30,395.63,4.32,30.80},
-        {0.03359,75.00,2.950,0,0.4280,7.0240,15.80,5.4011,3,252.0,18.30,395.62,1.98,34.90},
-        {0.12744,0.00,6.910,0,0.4480,6.7700,2.90,5.7209,3,233.0,17.90,385.41,4.84,26.60},
-        {0.14150,0.00,6.910,0,0.4480,6.1690,6.60,5.7209,3,233.0,17.90,383.37,5.81,25.30},
-        {0.15936,0.00,6.910,0,0.4480,6.2110,6.50,5.7209,3,233.0,17.90,394.46,7.44,24.70},
-        {0.12269,0.00,6.910,0,0.4480,6.0690,40.00,5.7209,3,233.0,17.90,389.39,9.55,21.20},
-        {0.17142,0.00,6.910,0,0.4480,5.6820,33.80,5.1004,3,233.0,17.90,396.90,10.21,19.30},
-        {0.18836,0.00,6.910,0,0.4480,5.7860,33.30,5.1004,3,233.0,17.90,396.90,14.15,20.00},
-        {0.22927,0.00,6.910,0,0.4480,6.0300,85.50,5.6894,3,233.0,17.90,392.74,18.80,16.60},
-        {0.25387,0.00,6.910,0,0.4480,5.3990,95.30,5.8700,3,233.0,17.90,396.90,30.81,14.40},
-        {0.21977,0.00,6.910,0,0.4480,5.6020,62.00,6.0877,3,233.0,17.90,396.90,16.20,19.40},
-        {0.08873,21.00,5.640,0,0.4390,5.9630,45.70,6.8147,4,243.0,16.80,395.56,13.45,19.70},
-        {0.04337,21.00,5.640,0,0.4390,6.1150,63.00,6.8147,4,243.0,16.80,393.97,9.43,20.50},
-        {0.05360,21.00,5.640,0,0.4390,6.5110,21.10,6.8147,4,243.0,16.80,396.90,5.28,25.00},
-        {0.04981,21.00,5.640,0,0.4390,5.9980,21.40,6.8147,4,243.0,16.80,396.90,8.43,23.40},
-        {0.01360,75.00,4.000,0,0.4100,5.8880,47.60,7.3197,3,469.0,21.10,396.90,14.80,18.90},
-        {0.01311,90.00,1.220,0,0.4030,7.2490,21.90,8.6966,5,226.0,17.90,395.93,4.81,35.40},
-        {0.02055,85.00,0.740,0,0.4100,6.3830,35.70,9.1876,2,313.0,17.30,396.90,5.77,24.70},
-        {0.01432,100.00,1.320,0,0.4110,6.8160,40.50,8.3248,5,256.0,15.10,392.90,3.95,31.60},
-        {0.15445,25.00,5.130,0,0.4530,6.1450,29.20,7.8148,8,284.0,19.70,390.68,6.86,23.30},
-        {0.10328,25.00,5.130,0,0.4530,5.9270,47.20,6.9320,8,284.0,19.70,396.90,9.22,19.60},
-        {0.14932,25.00,5.130,0,0.4530,5.7410,66.20,7.2254,8,284.0,19.70,395.11,13.15,18.70},
-        {0.17171,25.00,5.130,0,0.4530,5.9660,93.40,6.8185,8,284.0,19.70,378.08,14.44,16.00},
-        {0.11027,25.00,5.130,0,0.4530,6.4560,67.80,7.2255,8,284.0,19.70,396.90,6.73,22.20},
-        {0.12650,25.00,5.130,0,0.4530,6.7620,43.40,7.9809,8,284.0,19.70,395.58,9.50,25.00},
-        {0.01951,17.50,1.380,0,0.4161,7.1040,59.50,9.2229,3,216.0,18.60,393.24,8.05,33.00},
-        {0.03584,80.00,3.370,0,0.3980,6.2900,17.80,6.6115,4,337.0,16.10,396.90,4.67,23.50},
-        {0.04379,80.00,3.370,0,0.3980,5.7870,31.10,6.6115,4,337.0,16.10,396.90,10.24,19.40},
-        {0.05789,12.50,6.070,0,0.4090,5.8780,21.40,6.4980,4,345.0,18.90,396.21,8.10,22.00},
-        {0.13554,12.50,6.070,0,0.4090,5.5940,36.80,6.4980,4,345.0,18.90,396.90,13.09,17.40},
-        {0.12816,12.50,6.070,0,0.4090,5.8850,33.00,6.4980,4,345.0,18.90,396.90,8.79,20.90},
-        {0.08826,0.00,10.810,0,0.4130,6.4170,6.60,5.2873,4,305.0,19.20,383.73,6.72,24.20},
-        {0.15876,0.00,10.810,0,0.4130,5.9610,17.50,5.2873,4,305.0,19.20,376.94,9.88,21.70},
-        {0.09164,0.00,10.810,0,0.4130,6.0650,7.80,5.2873,4,305.0,19.20,390.91,5.52,22.80},
-        {0.19539,0.00,10.810,0,0.4130,6.2450,6.20,5.2873,4,305.0,19.20,377.17,7.54,23.40},
-        {0.07896,0.00,12.830,0,0.4370,6.2730,6.00,4.2515,5,398.0,18.70,394.92,6.78,24.10},
-        {0.09512,0.00,12.830,0,0.4370,6.2860,45.00,4.5026,5,398.0,18.70,383.23,8.94,21.40},
-        {0.10153,0.00,12.830,0,0.4370,6.2790,74.50,4.0522,5,398.0,18.70,373.66,11.97,20.00},
-        {0.08707,0.00,12.830,0,0.4370,6.1400,45.80,4.0905,5,398.0,18.70,386.96,10.27,20.80},
-        {0.05646,0.00,12.830,0,0.4370,6.2320,53.70,5.0141,5,398.0,18.70,386.40,12.34,21.20},
-        {0.08387,0.00,12.830,0,0.4370,5.8740,36.60,4.5026,5,398.0,18.70,396.06,9.10,20.30},
-        {0.04113,25.00,4.860,0,0.4260,6.7270,33.50,5.4007,4,281.0,19.00,396.90,5.29,28.00},
-        {0.04462,25.00,4.860,0,0.4260,6.6190,70.40,5.4007,4,281.0,19.00,395.63,7.22,23.90},
-        {0.03659,25.00,4.860,0,0.4260,6.3020,32.20,5.4007,4,281.0,19.00,396.90,6.72,24.80},
-        {0.03551,25.00,4.860,0,0.4260,6.1670,46.70,5.4007,4,281.0,19.00,390.64,7.51,22.90},
-        {0.05059,0.00,4.490,0,0.4490,6.3890,48.00,4.7794,3,247.0,18.50,396.90,9.62,23.90},
-        {0.05735,0.00,4.490,0,0.4490,6.6300,56.10,4.4377,3,247.0,18.50,392.30,6.53,26.60},
-        {0.05188,0.00,4.490,0,0.4490,6.0150,45.10,4.4272,3,247.0,18.50,395.99,12.86,22.50},
-        {0.07151,0.00,4.490,0,0.4490,6.1210,56.80,3.7476,3,247.0,18.50,395.15,8.44,22.20},
-        {0.05660,0.00,3.410,0,0.4890,7.0070,86.30,3.4217,2,270.0,17.80,396.90,5.50,23.60},
-        {0.05302,0.00,3.410,0,0.4890,7.0790,63.10,3.4145,2,270.0,17.80,396.06,5.70,28.70},
-        {0.04684,0.00,3.410,0,0.4890,6.4170,66.10,3.0923,2,270.0,17.80,392.18,8.81,22.60},
-        {0.03932,0.00,3.410,0,0.4890,6.4050,73.90,3.0921,2,270.0,17.80,393.55,8.20,22.00},
-        {0.04203,28.00,15.040,0,0.4640,6.4420,53.60,3.6659,4,270.0,18.20,395.01,8.16,22.90},
-        {0.02875,28.00,15.040,0,0.4640,6.2110,28.90,3.6659,4,270.0,18.20,396.33,6.21,25.00},
-        {0.04294,28.00,15.040,0,0.4640,6.2490,77.30,3.6150,4,270.0,18.20,396.90,10.59,20.60},
-        {0.12204,0.00,2.890,0,0.4450,6.6250,57.80,3.4952,2,276.0,18.00,357.98,6.65,28.40},
-        {0.11504,0.00,2.890,0,0.4450,6.1630,69.60,3.4952,2,276.0,18.00,391.83,11.34,21.40},
-        {0.12083,0.00,2.890,0,0.4450,8.0690,76.00,3.4952,2,276.0,18.00,396.90,4.21,38.70},
-        {0.08187,0.00,2.890,0,0.4450,7.8200,36.90,3.4952,2,276.0,18.00,393.53,3.57,43.80},
-        {0.06860,0.00,2.890,0,0.4450,7.4160,62.50,3.4952,2,276.0,18.00,396.90,6.19,33.20},
-        {0.14866,0.00,8.560,0,0.5200,6.7270,79.90,2.7778,5,384.0,20.90,394.76,9.42,27.50},
-        {0.11432,0.00,8.560,0,0.5200,6.7810,71.30,2.8561,5,384.0,20.90,395.58,7.67,26.50},
-        {0.22876,0.00,8.560,0,0.5200,6.4050,85.40,2.7147,5,384.0,20.90,70.80,10.63,18.60},
-        {0.21161,0.00,8.560,0,0.5200,6.1370,87.40,2.7147,5,384.0,20.90,394.47,13.44,19.30},
-        {0.13960,0.00,8.560,0,0.5200,6.1670,90.00,2.4210,5,384.0,20.90,392.69,12.33,20.10},
-        {0.13262,0.00,8.560,0,0.5200,5.8510,96.70,2.1069,5,384.0,20.90,394.05,16.47,19.50},
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-        {0.22438,0.00,9.690,0,0.5850,6.0270,79.70,2.4982,6,391.0,19.20,396.90,14.33,16.80},
-        {0.06263,0.00,11.930,0,0.5730,6.5930,69.10,2.4786,1,273.0,21.00,391.99,9.67,22.40},
-        {0.04527,0.00,11.930,0,0.5730,6.1200,76.70,2.2875,1,273.0,21.00,396.90,9.08,20.60},
-        {0.06076,0.00,11.930,0,0.5730,6.9760,91.00,2.1675,1,273.0,21.00,396.90,5.64,23.90},
-        {0.10959,0.00,11.930,0,0.5730,6.7940,89.30,2.3889,1,273.0,21.00,393.45,6.48,22.00},
-        {0.04741,0.00,11.930,0,0.5730,6.0300,80.80,2.5050,1,273.0,21.00,396.90,7.88,11.90}
-    };
 }

http://git-wip-us.apache.org/repos/asf/ignite/blob/370cd3e1/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java
----------------------------------------------------------------------
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java b/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java
new file mode 100644
index 0000000..b7380e0
--- /dev/null
+++ b/examples/src/main/java/org/apache/ignite/examples/ml/util/MLSandboxDatasets.java
@@ -0,0 +1,87 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.ignite.examples.ml.util;
+
+/**
+ * The names of popular datasets used in examples.
+ */
+public enum MLSandboxDatasets {
+    /** The full Iris dataset from Machine Learning Repository. */
+    IRIS("examples/src/main/resources/datasets/iris.txt", false, "\t"),
+
+    /** The Titanic dataset from Kaggle competition. */
+    TITANIC("examples/src/main/resources/datasets/titanic.csv", true, ";"),
+
+    /** The 1st and 2nd classes from the Iris dataset. */
+    TWO_CLASSED_IRIS("examples/src/main/resources/datasets/two_classed_iris.csv", false, "\t"),
+
+    /** The dataset is about different computers' properties based on https://archive.ics.uci.edu/ml/datasets/Computer+Hardware. */
+    CLEARED_MACHINES("examples/src/main/resources/datasets/cleared_machines.csv", false, ";"),
+
+    /**
+     * The health data is related to death rate based on; doctor availability, hospital availability,
+     * annual per capita income, and population density people per square mile.
+     */
+    MORTALITY_DATA("examples/src/main/resources/datasets/mortalitydata.csv", false, ";"),
+
+    /**
+     * The preprocessed Glass dataset from the Machine Learning Repository https://archive.ics.uci.edu/ml/datasets/Glass+Identification
+     * There are 3 classes with labels: 1 {building_windows_float_processed}, 3 {vehicle_windows_float_processed}, 7 {headlamps}.
+     * Feature names: 'Na-Sodium', 'Mg-Magnesium', 'Al-Aluminum', 'Ba-Barium', 'Fe-Iron'.
+     */
+    GLASS_IDENTIFICATION("examples/src/main/resources/datasets/glass_identification.csv", false, ";"),
+
+    /** The Wine recognition data. Could be found <a href="https://archive.ics.uci.edu/ml/machine-learning-databases/wine/">here</a>. */
+    WINE_RECOGNITION("examples/src/main/resources/datasets/wine.txt", false, ","),
+
+    /** The Boston house-prices dataset. Could be found <a href="https://archive.ics.uci.edu/ml/machine-learning-databases/housing/">here</a>. */
+    BOSTON_HOUSE_PRICES("examples/src/main/resources/datasets/boston_housing_dataset.txt", false, ",");
+
+    /** Filename. */
+    private final String filename;
+
+    /** The csv file has header. */
+    private final boolean hasHeader;
+
+    /** The separator between words. */
+    private final String separator;
+
+    /**
+     * @param filename Filename.
+     * @param hasHeader The csv file has header.
+     * @param separator The special sign to separate the line on words.
+     */
+    MLSandboxDatasets(final String filename, boolean hasHeader, String separator) {
+        this.filename = filename;
+        this.hasHeader = hasHeader;
+        this.separator = separator;
+    }
+
+    /** */
+    public String getFileName() { return filename; }
+
+    /** */
+    public boolean hasHeader() {
+        return hasHeader;
+    }
+
+    /** */
+    public String getSeparator() {
+        return separator;
+    }
+}

http://git-wip-us.apache.org/repos/asf/ignite/blob/370cd3e1/examples/src/main/java/org/apache/ignite/examples/ml/util/SandboxMLCache.java
----------------------------------------------------------------------
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/util/SandboxMLCache.java b/examples/src/main/java/org/apache/ignite/examples/ml/util/SandboxMLCache.java
new file mode 100644
index 0000000..cc607be
--- /dev/null
+++ b/examples/src/main/java/org/apache/ignite/examples/ml/util/SandboxMLCache.java
@@ -0,0 +1,144 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.ignite.examples.ml.util;
+
+import java.io.File;
+import java.io.FileNotFoundException;
+import java.nio.file.Paths;
+import java.text.NumberFormat;
+import java.text.ParseException;
+import java.util.Locale;
+import java.util.Scanner;
+import java.util.UUID;
+import org.apache.ignite.Ignite;
+import org.apache.ignite.IgniteCache;
+import org.apache.ignite.cache.affinity.rendezvous.RendezvousAffinityFunction;
+import org.apache.ignite.configuration.CacheConfiguration;
+import org.apache.ignite.ml.math.exceptions.knn.FileParsingException;
+import org.apache.ignite.ml.math.primitives.vector.Vector;
+import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
+
+
+/**
+ * Common utility code used in some ML examples to set up test cache.
+ */
+public class SandboxMLCache {
+    /** */
+    private final Ignite ignite;
+
+    /** */
+    public SandboxMLCache(Ignite ignite) {
+        this.ignite = ignite;
+    }
+
+    /**
+     * Fills cache with data and returns it.
+     *
+     * @param data Data to fill the cache with.
+     * @return Filled Ignite Cache.
+     */
+    public IgniteCache<Integer, double[]> fillCacheWith(double[][] data) {
+        CacheConfiguration<Integer, double[]> cacheConfiguration = new CacheConfiguration<>();
+        cacheConfiguration.setName("TEST_" + UUID.randomUUID());
+        cacheConfiguration.setAffinity(new RendezvousAffinityFunction(false, 10));
+
+        IgniteCache<Integer, double[]> cache = ignite.createCache(cacheConfiguration);
+
+        for (int i = 0; i < data.length; i++)
+            cache.put(i, data[i]);
+
+        return cache;
+    }
+
+    /**
+     * Fills cache with data and returns it.
+     *
+     * @param data Data to fill the cache with.
+     * @return Filled Ignite Cache.
+     */
+    public IgniteCache<Integer, Vector> getVectors(double[][] data) {
+        CacheConfiguration<Integer, Vector> cacheConfiguration = new CacheConfiguration<>();
+        cacheConfiguration.setName("TEST_" + UUID.randomUUID());
+        cacheConfiguration.setAffinity(new RendezvousAffinityFunction(false, 10));
+
+        IgniteCache<Integer, Vector> cache = ignite.createCache(cacheConfiguration);
+
+        for (int i = 0; i < data.length; i++)
+            cache.put(i, VectorUtils.of(data[i]));
+
+        return cache;
+    }
+
+    /**
+     * Fills cache with data and returns it.
+     *
+     * @param dataset The chosen dataset.
+     * @return Filled Ignite Cache.
+     * @throws FileNotFoundException If file not found.
+     */
+    public IgniteCache<Integer, Vector> fillCacheWith(MLSandboxDatasets dataset) throws FileNotFoundException {
+
+        IgniteCache<Integer, Vector> cache = getCache();
+
+        Scanner scanner = new Scanner(new File(dataset.getFileName()));
+
+        int cnt = 0;
+        while (scanner.hasNextLine()) {
+            String row = scanner.nextLine();
+            if(dataset.hasHeader() && cnt == 0) {
+                cnt++;
+                continue;
+            }
+
+            String[] cells = row.split(dataset.getSeparator());
+
+            double[] data = new double[cells.length];
+            NumberFormat format = NumberFormat.getInstance(Locale.FRANCE);
+
+            for (int i = 0; i < cells.length; i++)
+                try{
+                    if(cells[i].equals("")) data[i] = Double.NaN;
+                    else data[i] = Double.valueOf(cells[i]);
+                } catch (java.lang.NumberFormatException e) {
+                    try {
+                        data[i] = format.parse(cells[i]).doubleValue();
+                    }
+                    catch (ParseException e1) {
+                        throw new FileParsingException(cells[i], i, Paths.get(dataset.getFileName()));
+                    }
+                }
+            cache.put(cnt++, VectorUtils.of(data));
+        }
+        return cache;
+
+    }
+
+    /**
+     * Fills cache with data and returns it.
+     *
+     * @return Filled Ignite Cache.
+     */
+    private IgniteCache<Integer, Vector> getCache() {
+
+        CacheConfiguration<Integer, Vector> cacheConfiguration = new CacheConfiguration<>();
+        cacheConfiguration.setName("TUTORIAL_" + UUID.randomUUID());
+        cacheConfiguration.setAffinity(new RendezvousAffinityFunction(false, 10));
+
+        return ignite.createCache(cacheConfiguration);
+    }
+}

http://git-wip-us.apache.org/repos/asf/ignite/blob/370cd3e1/examples/src/main/java/org/apache/ignite/examples/ml/util/TestCache.java
----------------------------------------------------------------------
diff --git a/examples/src/main/java/org/apache/ignite/examples/ml/util/TestCache.java b/examples/src/main/java/org/apache/ignite/examples/ml/util/TestCache.java
deleted file mode 100644
index 454aa76..0000000
--- a/examples/src/main/java/org/apache/ignite/examples/ml/util/TestCache.java
+++ /dev/null
@@ -1,77 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements.  See the NOTICE file distributed with
- * this work for additional information regarding copyright ownership.
- * The ASF licenses this file to You under the Apache License, Version 2.0
- * (the "License"); you may not use this file except in compliance with
- * the License.  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package org.apache.ignite.examples.ml.util;
-
-import java.util.UUID;
-import org.apache.ignite.Ignite;
-import org.apache.ignite.IgniteCache;
-import org.apache.ignite.cache.affinity.rendezvous.RendezvousAffinityFunction;
-import org.apache.ignite.configuration.CacheConfiguration;
-import org.apache.ignite.ml.math.primitives.vector.Vector;
-import org.apache.ignite.ml.math.primitives.vector.VectorUtils;
-
-/**
- * Common utility code used in some ML examples to set up test cache.
- */
-public class TestCache {
-    /** */
-    private final Ignite ignite;
-
-    /** */
-    public TestCache(Ignite ignite) {
-        this.ignite = ignite;
-    }
-
-    /**
-     * Fills cache with data and returns it.
-     *
-     * @param data Data to fill the cache with.
-     * @return Filled Ignite Cache.
-     */
-    public IgniteCache<Integer, double[]> fillCacheWith(double[][] data) {
-        CacheConfiguration<Integer, double[]> cacheConfiguration = new CacheConfiguration<>();
-        cacheConfiguration.setName("TEST_" + UUID.randomUUID());
-        cacheConfiguration.setAffinity(new RendezvousAffinityFunction(false, 10));
-
-        IgniteCache<Integer, double[]> cache = ignite.createCache(cacheConfiguration);
-
-        for (int i = 0; i < data.length; i++)
-            cache.put(i, data[i]);
-
-        return cache;
-    }
-
-    /**
-     * Fills cache with data and returns it.
-     *
-     * @param data Data to fill the cache with.
-     * @return Filled Ignite Cache.
-     */
-    public IgniteCache<Integer, Vector> getVectors(double[][] data) {
-        CacheConfiguration<Integer, Vector> cacheConfiguration = new CacheConfiguration<>();
-        cacheConfiguration.setName("TEST_" + UUID.randomUUID());
-        cacheConfiguration.setAffinity(new RendezvousAffinityFunction(false, 10));
-
-        IgniteCache<Integer, Vector> cache = ignite.createCache(cacheConfiguration);
-
-        for (int i = 0; i < data.length; i++)
-            cache.put(i, VectorUtils.of(data[i]));
-
-        return cache;
-    }
-}


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