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[ML] relaxing parameters on stratified split test #54127

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Mar 25, 2020
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[ML] relaxing parameters on stratified split test #54127

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6 changes: 3 additions & 3 deletions ...ch/xpack/ml/dataframe/process/crossvalidation/StratifiedCrossValidationSplitterTests.java
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Original file line number Diff line number Diff line change
Expand Up @@ -179,8 +179,8 @@ public void testProcess_GivenRowsWithDependentVariableValue_AndTrainingPercentIs

double expectedTotalTrainingCount = ROWS_COUNT * trainingFraction;
assertThat(trainingDocsCount + testDocsCount, equalTo((long) ROWS_COUNT));
assertThat(trainingDocsCount, greaterThanOrEqualTo((long) Math.floor(expectedTotalTrainingCount - 1)));
assertThat(trainingDocsCount, lessThanOrEqualTo((long) Math.ceil(expectedTotalTrainingCount + 1)));
assertThat(trainingDocsCount, greaterThanOrEqualTo((long) (expectedTotalTrainingCount - 2)));
assertThat(trainingDocsCount, lessThanOrEqualTo((long) Math.ceil(expectedTotalTrainingCount) + 2));

for (String classValue : classCardinalities.keySet()) {
double expectedClassTrainingCount = totalRowsPerClass.get(classValue) * trainingFraction;
Expand Down Expand Up @@ -221,7 +221,7 @@ public void testProcess_SelectsTrainingRowsUniformly() {
// should be close to the training percent, which is set to 0.5
for (int rowTrainingCount : trainingCountPerRow) {
double meanCount = rowTrainingCount / (double) runCount;
assertThat(meanCount, is(closeTo(0.5, 0.1)));
assertThat(meanCount, is(closeTo(0.5, 0.12)));
}
}

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