All threshold as null in F1 Score.

src/TensorFlowNET.Core/Keras/Metrics/IMetricsApi.cs

@@ -77,7 +77,7 @@ public interface IMetricsApi
     /// <returns></returns>
     IMetricFunc F1Score(int num_classes,
         string? average = null,
-        float threshold = -1f,
+        float? threshold = null,
         string name = "f1_score",
         TF_DataType dtype = TF_DataType.TF_FLOAT);
 
@@ -88,7 +88,7 @@ public interface IMetricsApi
     IMetricFunc FBetaScore(int num_classes, 
         string? average = null,
         float beta = 0.1f,
-        float threshold = -1f,
+        float? threshold = null,
         string name = "fbeta_score",
         TF_DataType dtype = TF_DataType.TF_FLOAT);
     

src/TensorFlowNET.Keras/Metrics/F1Score.cs

@@ -4,7 +4,7 @@ public class F1Score : FBetaScore
 {
     public F1Score(int num_classes,
         string? average = null,
-        float? threshold = -1f,
+        float? threshold = null,
         string name = "f1_score",
         TF_DataType dtype = TF_DataType.TF_FLOAT)
         : base(num_classes, average: average, threshold: threshold, beta: 1f, name: name, dtype: dtype)

src/TensorFlowNET.Keras/Metrics/FBetaScore.cs

@@ -17,7 +17,7 @@ public class FBetaScore : Metric
     public FBetaScore(int num_classes,
         string? average = null,
         float beta = 0.1f,
-        float? threshold = -1f,
+        float? threshold = null,
         string name = "fbeta_score",
         TF_DataType dtype = TF_DataType.TF_FLOAT)
         : base(name: name, dtype: dtype)

src/TensorFlowNET.Keras/Metrics/MetricsApi.cs

@@ -86,10 +86,10 @@
         public IMetricFunc CosineSimilarity(string name = "cosine_similarity", TF_DataType dtype = TF_DataType.TF_FLOAT, Axis? axis = null)
             => new CosineSimilarity(name: name, dtype: dtype, axis: axis ?? -1);
 
-        public IMetricFunc F1Score(int num_classes, string? average = null, float threshold = -1, string name = "f1_score", TF_DataType dtype = TF_DataType.TF_FLOAT)
+        public IMetricFunc F1Score(int num_classes, string? average = null, float? threshold = null, string name = "f1_score", TF_DataType dtype = TF_DataType.TF_FLOAT)
             => new F1Score(num_classes, average: average, threshold: threshold, name: name, dtype: dtype);
 
-        public IMetricFunc FBetaScore(int num_classes, string? average = null, float beta = 0.1F, float threshold = -1, string name = "fbeta_score", TF_DataType dtype = TF_DataType.TF_FLOAT)
+        public IMetricFunc FBetaScore(int num_classes, string? average = null, float beta = 0.1F, float? threshold = null, string name = "fbeta_score", TF_DataType dtype = TF_DataType.TF_FLOAT)
             => new FBetaScore(num_classes, average: average,beta: beta, threshold: threshold, name: name, dtype: dtype);
 
         public IMetricFunc TopKCategoricalAccuracy(int k = 5, string name = "top_k_categorical_accuracy", TF_DataType dtype = TF_DataType.TF_FLOAT)