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[ML] Missing variable initialisation causing spurious model reinitialisation for lat/long function #641

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Sep 4, 2019
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[ML] Missing variable initialisation causing spurious model reinitialisation for lat/long function #641

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Missing variable initialisation
tveasey Sep 4, 2019
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tveasey Sep 4, 2019
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2 changes: 2 additions & 0 deletions docs/CHANGELOG.asciidoc
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,8 @@ train time. (See {ml-pull}622[#622].)

* Rename outlier detection method values knn and tnn to distance_kth_nn and distance_knn
respectively to match the API. (See {ml-pull}598[#598].)
* Fix occasional (non-deterministic) reinitialisation of modelling for the lat_long
function. (See {ml-pull}641[#641].)

== {es} version 7.3.1

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5 changes: 2 additions & 3 deletions lib/maths/CTimeSeriesModel.cc
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Expand Up @@ -1607,8 +1607,6 @@ CUnivariateTimeSeriesModel::updateTrend(const TTimeDouble2VecSizeTrVec& samples,
}
}

EUpdateResult result = E_Success;

// Time order is not reliable, for example if the data are polled
// or for count feature, the times of all samples will be the same.
TSizeVec timeorder(samples.size());
Expand All @@ -1623,6 +1621,7 @@ CUnivariateTimeSeriesModel::updateTrend(const TTimeDouble2VecSizeTrVec& samples,
// Do the update.

TFloatMeanAccumulatorVec window;
EUpdateResult result{E_Success};
auto componentChangeCallback = [&window, &result](TFloatMeanAccumulatorVec window_) {
window = std::move(window_);
result = E_Reset;
Expand Down Expand Up @@ -2944,7 +2943,7 @@ CMultivariateTimeSeriesModel::updateTrend(const TTimeDouble2VecSizeTrVec& sample

// Do the update.

EUpdateResult result;
EUpdateResult result{E_Success};
auto componentChangeCallback = [&result](TFloatMeanAccumulatorVec) {
result = E_Reset;
};
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