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author | yazevnul <yazevnul@yandex-team.ru> | 2022-02-10 16:46:46 +0300 |
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committer | Daniil Cherednik <dcherednik@yandex-team.ru> | 2022-02-10 16:46:46 +0300 |
commit | 8cbc307de0221f84c80c42dcbe07d40727537e2c (patch) | |
tree | 625d5a673015d1df891e051033e9fcde5c7be4e5 /library/cpp/linear_regression/linear_regression.h | |
parent | 30d1ef3941e0dc835be7609de5ebee66958f215a (diff) | |
download | ydb-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.h | 10 |
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.; } }; |