[CodeFactor] Apply fixes

lib/errors/Huber.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///     Peter J. Huber - "Robust Estimation of a Location Parameter"
 ///     https://projecteuclid.org/euclid.aoms/1177703732
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Huber : AbstractBase
 {

lib/errors/Mae.cs

@@ -27,7 +27,6 @@ namespace QuanTAlib;
 ///     https://en.wikipedia.org/wiki/Mean_absolute_error
 ///     https://www.statisticshowto.com/absolute-error/
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mae : AbstractBase
 {

lib/errors/Mapd.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Also known as MAPE (Mean Absolute Percentage Error) in some contexts
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mapd : AbstractBase
 {

lib/errors/Mape.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Also known as MAPD (Mean Absolute Percentage Deviation) in some contexts
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mape : AbstractBase
 {

lib/errors/Mase.cs

@@ -28,7 +28,6 @@ namespace QuanTAlib;
 ///     Rob J. Hyndman - "Another Look at Forecast-Accuracy Metrics for Intermittent Demand"
 ///     https://robjhyndman.com/papers/another-look-at-measures-of-forecast-accuracy/
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mase : AbstractBase
 {

lib/errors/Mda.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///     https://www.sciencedirect.com/science/article/abs/pii/S0169207016000121
 ///     "Evaluating Forecasting Performance" - International Journal of Forecasting
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mda : AbstractBase
 {

lib/errors/Me.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Also known as Mean Bias Error (MBE) or Mean Signed Difference (MSD)
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Me : AbstractBase
 {

lib/errors/Mpe.cs

@@ -30,7 +30,6 @@ namespace QuanTAlib;
 ///
 /// Note: Similar to MAPE but allows error cancellation
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mpe : AbstractBase
 {

lib/errors/Mse.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Often used in optimization due to its mathematical properties
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Mse : AbstractBase
 {

lib/errors/Msle.cs

@@ -30,7 +30,6 @@ namespace QuanTAlib;
 ///
 /// Note: Often used in cases where target values follow exponential growth
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Msle : AbstractBase
 {

lib/errors/Rae.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Values greater than 1 indicate predictions worse than using zero
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Rae : AbstractBase
 {

lib/errors/Rmse.cs

@@ -30,7 +30,6 @@ namespace QuanTAlib;
 ///
 /// Note: Square root of MSE, making it more interpretable in original units
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Rmse : AbstractBase
 {

lib/errors/Rmsle.cs

@@ -31,7 +31,6 @@ namespace QuanTAlib;
 ///
 /// Note: Square root of MSLE, useful for data with exponential growth
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Rmsle : AbstractBase
 {

lib/errors/Rse.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Values less than 1 indicate predictions better than using mean
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Rse : AbstractBase
 {

lib/errors/Rsquared.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: Can be negative if predictions are worse than using the mean
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Rsquared : AbstractBase
 {

lib/errors/Smape.cs

@@ -29,7 +29,6 @@ namespace QuanTAlib;
 ///
 /// Note: More stable than MAPE when actual values are close to zero
 /// </remarks>
-
 [SkipLocalsInit]
 public sealed class Smape : AbstractBase
 {