//バッチで学習処理を行う
public static Real Train(FunctionStack functionStack, Array[] input, Array[] teach, LossFunction lossFunction, bool isUpdate = true)
{
return(Train(functionStack, NdArray.FromArrays(input), NdArray.FromArrays(teach), lossFunction, isUpdate));
}
//精度測定
public static double Accuracy(FunctionStack functionStack, Array[] x, Array[] y)
{
return(Accuracy(functionStack, NdArray.FromArrays(x), NdArray.FromArrays(y)));
}
//精度測定
public static T Accuracy <T>(FunctionStack <T> functionStack, T[][] x, int[][] y) where T : unmanaged, IComparable <T>
{
return(Accuracy(functionStack, NdArray.FromArrays(x), NdArray.FromArrays(y)));
}
//精度測定
public static T Accuracy <T>(FunctionStack <T> functionStack, T[][] x, int[][] y, LossFunction <T, int> lossFunction, out T loss) where T : unmanaged, IComparable <T>
{
return(Accuracy(functionStack, NdArray.FromArrays(x), NdArray.FromArrays(y), lossFunction, out loss));
}
//バッチで学習処理を行う
public static T Train <T, LabelType>(FunctionStack <T> functionStack, T[][] input, LabelType[][] teach, LossFunction <T, LabelType> lossFunction, Optimizer <T> optimizer = null) where T : unmanaged, IComparable <T> where LabelType : unmanaged, IComparable <LabelType>
{
return(Train(functionStack, NdArray.FromArrays(input), NdArray.FromArrays(teach), lossFunction, optimizer));
}