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new 6a318ecee6 [MINOR] Additional real-data decision tree tests (existing
datasets)
6a318ecee6 is described below
commit 6a318ecee624ab448951f53bb9f4443bb510c4ad
Author: Matthias Boehm <[email protected]>
AuthorDate: Sun Jun 11 21:28:11 2023 +0200
[MINOR] Additional real-data decision tree tests (existing datasets)
---
.../part1/BuiltinDecisionTreeRealDataTest.java | 18 +++++++-
src/test/resources/datasets/EEG_tfspec.json | 19 +++++++++
.../functions/builtin/decisionTreeRealData4.dml | 49 ++++++++++++++++++++++
3 files changed, 84 insertions(+), 2 deletions(-)
diff --git
a/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinDecisionTreeRealDataTest.java
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinDecisionTreeRealDataTest.java
index 41bd6c651a..58ad08b625 100644
---
a/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinDecisionTreeRealDataTest.java
+++
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinDecisionTreeRealDataTest.java
@@ -37,10 +37,12 @@ public class BuiltinDecisionTreeRealDataTest extends
AutomatedTestBase {
private final static String TITANIC_TFSPEC = DATASET_DIR +
"titanic/tfspec.json";
private final static String WINE_DATA = DATASET_DIR +
"wine/winequality-red-white.csv";
private final static String WINE_TFSPEC = DATASET_DIR +
"wine/tfspec.json";
+ private final static String EEG_DATA = DATASET_DIR + "EEG.csv";
+ private final static String EEG_TFSPEC = DATASET_DIR +
"EEG_tfspec.json";
@Override
public void setUp() {
- for(int i=1; i<=3; i++)
+ for(int i=1; i<=4; i++)
addTestConfiguration(TEST_NAME+i, new
TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[] {"R"}));
}
@@ -99,12 +101,24 @@ public class BuiltinDecisionTreeRealDataTest extends
AutomatedTestBase {
//for regression we compare R2 and use rss to optimize
runDecisionTree(3, WINE_DATA, WINE_TFSPEC, 0.369, 2, 1.0,
ExecType.CP);
}
+
+ @Test
+ public void testDecisionTreeEEG_MaxV1() {
+ //for regression we compare R2 and use rss to optimize
+ runDecisionTree(4, EEG_DATA, EEG_TFSPEC, 0.62, 1, 1.0,
ExecType.CP);
+ }
+
+ @Test
+ public void testRandomForestEEG_MaxV1() {
+ //for regression we compare R2 and use rss to optimize
+ runDecisionTree(4, EEG_DATA, EEG_TFSPEC, 0.62, 2, 1.0,
ExecType.CP);
+ }
private void runDecisionTree(int test, String data, String tfspec,
double minAcc, int dt, double maxV, ExecType instType) {
Types.ExecMode platformOld = setExecMode(instType);
try {
loadTestConfiguration(getTestConfiguration(TEST_NAME+test));
-
+
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + (TEST_NAME+test) + ".dml";
programArgs = new String[] {"-stats",
diff --git a/src/test/resources/datasets/EEG_tfspec.json
b/src/test/resources/datasets/EEG_tfspec.json
new file mode 100644
index 0000000000..361d0a85a1
--- /dev/null
+++ b/src/test/resources/datasets/EEG_tfspec.json
@@ -0,0 +1,19 @@
+{
+ "ids":true,
+ "recode":[1],
+ "bin":[
+ {"id":2, "method":"equi-width", "numbins":100},
+ {"id":3, "method":"equi-width", "numbins":100},
+ {"id":4, "method":"equi-width", "numbins":100},
+ {"id":5, "method":"equi-width", "numbins":100},
+ {"id":6, "method":"equi-width", "numbins":100},
+ {"id":7, "method":"equi-width", "numbins":100},
+ {"id":8, "method":"equi-width", "numbins":100},
+ {"id":9, "method":"equi-width", "numbins":100},
+ {"id":10, "method":"equi-width", "numbins":100},
+ {"id":11, "method":"equi-width", "numbins":100},
+ {"id":12, "method":"equi-width", "numbins":100},
+ {"id":13, "method":"equi-width", "numbins":100},
+ {"id":14, "method":"equi-width", "numbins":100},
+ {"id":15, "method":"equi-width", "numbins":100},]
+}
diff --git a/src/test/scripts/functions/builtin/decisionTreeRealData4.dml
b/src/test/scripts/functions/builtin/decisionTreeRealData4.dml
new file mode 100644
index 0000000000..e1429f6499
--- /dev/null
+++ b/src/test/scripts/functions/builtin/decisionTreeRealData4.dml
@@ -0,0 +1,49 @@
+#-------------------------------------------------------------
+#
+# 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.
+#
+#-------------------------------------------------------------
+
+F = read($1, data_type="frame", format="csv", header=TRUE);
+tfspec = read($2, data_type="scalar", value_type="string");
+
+R = matrix("1 1 1 1 1 1 1 1 1 1 1 1 1 1 2", rows=1, cols=15)
+
+[X, meta] = transformencode(target=F, spec=tfspec);
+Y = X[, 1]
+X = X[, 2:ncol(X)]
+X = imputeByMode(X);
+
+if( $3==1 ) {
+ M = decisionTree(X=X, y=Y, ctypes=R, max_features=1, max_values=$4,
+ min_split=10, min_leaf=4, seed=7, verbose=TRUE);
+ yhat = decisionTreePredict(X=X, y=Y, ctypes=R, M=M)
+}
+else {
+ sf = 1.0/($3-1);
+ M = randomForest(X=X, y=Y, ctypes=R, sample_frac=sf, num_trees=$3-1,
+ max_features=1, max_values=$4,
+ min_split=10, min_leaf=4, seed=7, verbose=TRUE);
+ yhat = randomForestPredict(X=X, y=Y, ctypes=R, M=M)
+}
+
+acc = as.matrix(mean(yhat == Y))
+err = 1-(acc);
+print("accuracy: "+as.scalar(acc))
+
+write(acc, $5);
