Bias

8 writes to Bias

Microsoft.ML.StandardTrainers (8)

Standard\Online\AveragedLinear.cs (3)

213Bias = TotalBias / (float)NumWeightUpdates; 254Bias += biasUpdate; 272Bias = TotalBias / (float)NumWeightUpdates;

Standard\Online\LinearSvm.cs (2)

145Bias = 0; 238Bias += rate / _numBatchExamples * _biasUpdate;

Standard\Online\OnlineLinear.cs (3)

142Bias = predictor.Bias; 159Bias = float.Parse(weightStr[numFeatures], CultureInfo.InvariantCulture); 167Bias = parent.OnlineLinearTrainerOptions.InitialWeightsDiameter * (parent.Host.Rand.NextSingle() - (float)0.5);

13 references to Bias

Microsoft.ML.StandardTrainers (13)

Standard\Online\AveragedLinear.cs (4)

200TotalBias += Bias * NumNoUpdates; 237TotalBias += Bias * NumNoUpdates * WeightsScale; 285TotalBias += Bias; 290TotalBias += Gain * Bias;

Standard\Online\AveragedPerceptron.cs (1)

139bias = Bias;

Standard\Online\LinearSvm.cs (3)

236Contracts.Assert(!_noBias || Bias == 0); 258=> Bias + VectorUtils.DotProduct(in feat, in Weights) * WeightsScale; 264return new LinearBinaryModelParameters(ParentHost, Weights, Bias);

Standard\Online\OnlineGradientDescent.cs (1)

116bias = Bias;

Standard\Online\OnlineLinear.cs (4)

112/// The implicit scaling factor for <see cref="Weights"/>. Note that this does not affect <see cref="Bias"/>. 130ch.Assert(Bias == 0); 237=> Bias + VectorUtils.DotProduct(in feat, in Weights) * WeightsScale; 298float maxNorm = Math.Max(VectorUtils.MaxNorm(in state.Weights), Math.Abs(state.Bias));