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authoryazevnul <yazevnul@yandex-team.ru>2022-02-10 16:46:46 +0300
committerDaniil Cherednik <dcherednik@yandex-team.ru>2022-02-10 16:46:46 +0300
commit8cbc307de0221f84c80c42dcbe07d40727537e2c (patch)
tree625d5a673015d1df891e051033e9fcde5c7be4e5 /library/cpp/linear_regression/linear_regression.h
parent30d1ef3941e0dc835be7609de5ebee66958f215a (diff)
downloadydb-8cbc307de0221f84c80c42dcbe07d40727537e2c.tar.gz
Restoring authorship annotation for <yazevnul@yandex-team.ru>. Commit 1 of 2.
Diffstat (limited to 'library/cpp/linear_regression/linear_regression.h')
-rw-r--r--library/cpp/linear_regression/linear_regression.h10
1 files changed, 5 insertions, 5 deletions
diff --git a/library/cpp/linear_regression/linear_regression.h b/library/cpp/linear_regression/linear_regression.h
index e57de5ff6c..20b3ae1e53 100644
--- a/library/cpp/linear_regression/linear_regression.h
+++ b/library/cpp/linear_regression/linear_regression.h
@@ -146,12 +146,12 @@ public:
bool Add(const double* featuresBegin, const double* featuresEnd, const double* goalsBegin, const double* weightsBegin);
bool Add(const TVector<double>& features, const TVector<double>& goals) {
- Y_ASSERT(features.size() == goals.size());
+ Y_ASSERT(features.size() == goals.size());
return Add(features.data(), features.data() + features.size(), goals.data());
}
bool Add(const TVector<double>& features, const TVector<double>& goals, const TVector<double>& weights) {
- Y_ASSERT(features.size() == goals.size() && features.size() == weights.size());
+ Y_ASSERT(features.size() == goals.size() && features.size() == weights.size());
return Add(features.data(), features.data() + features.size(), goals.data(), weights.data());
}
@@ -239,7 +239,7 @@ struct TTransformationParameters {
double FeatureOffset = 0.;
double FeatureNormalizer = 1.;
- Y_SAVELOAD_DEFINE(RegressionFactor,
+ Y_SAVELOAD_DEFINE(RegressionFactor,
RegressionIntercept,
FeatureOffset,
FeatureNormalizer);
@@ -251,7 +251,7 @@ private:
TTransformationParameters TransformationParameters;
public:
- Y_SAVELOAD_DEFINE(TransformationType, TransformationParameters);
+ Y_SAVELOAD_DEFINE(TransformationType, TransformationParameters);
TFeaturesTransformer() = default;
@@ -273,7 +273,7 @@ public:
return TransformationParameters.RegressionIntercept + TransformationParameters.RegressionFactor * transformedValue;
}
}
- Y_ASSERT(0);
+ Y_ASSERT(0);
return 0.;
}
};