/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="layerSizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activFunc">各ニューロンの活性化関数</param>
/// <param name="fParam1">活性化関数のフリーパラメータα</param>
/// <param name="fParam2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
/// <param name="fParam1">Free parameter α of the activation function</param>
/// <param name="fParam2">Free parameter β of the activation function</param>
#endif
public CvANN_MLP(
CvMat layerSizes,
MLPActivationFunc activFunc = MLPActivationFunc.SigmoidSym,
double fParam1 = 0, double fParam2 = 0)
{
if (layerSizes == null)
throw new ArgumentNullException("layerSizes");
ptr = NativeMethods.ml_CvANN_MLP_new2_CvMat(
layerSizes.CvPtr, (int)activFunc, fParam1, fParam2);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="layerSizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activFunc">各ニューロンの活性化関数</param>
/// <param name="fParam1">活性化関数のフリーパラメータα</param>
/// <param name="fParam2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
/// <param name="fParam1">Free parameter α of the activation function</param>
/// <param name="fParam2">Free parameter β of the activation function</param>
#endif
public CvANN_MLP(
CvMat layerSizes,
MLPActivationFunc activFunc = MLPActivationFunc.SigmoidSym,
double fParam1 = 0, double fParam2 = 0)
{
if (layerSizes == null)
{
throw new ArgumentNullException("layerSizes");
}
ptr = NativeMethods.ml_CvANN_MLP_new2_CvMat(
layerSizes.CvPtr, (int)activFunc, fParam1, fParam2);
}
/// <summary>
/// 指定したトポロジーでMLPを構築する
/// </summary>
/// <param name="layerSizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activFunc">各ニューロンの活性化関数</param>
/// <param name="fParam1">活性化関数のフリーパラメータα</param>
/// <param name="fParam2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Constructs the MLP with the specified topology
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
/// <param name="fParam1">Free parameter α of the activation function</param>
/// <param name="fParam2">Free parameter β of the activation function</param>
#endif
public void Create(
Mat layerSizes,
MLPActivationFunc activFunc = MLPActivationFunc.SigmoidSym,
double fParam1 = 0, double fParam2 = 0)
{
if (disposed)
{
throw new ObjectDisposedException("StatModel");
}
if (layerSizes == null)
{
throw new ArgumentNullException("layerSizes");
}
layerSizes.ThrowIfDisposed();
NativeMethods.ml_CvANN_MLP_create_Mat(
ptr, layerSizes.CvPtr, (int)activFunc, fParam1, fParam2);
}
/// <summary>
/// 指定したトポロジーでMLPを構築する
/// </summary>
/// <param name="layerSizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activFunc">各ニューロンの活性化関数</param>
/// <param name="fParam1">活性化関数のフリーパラメータα</param>
/// <param name="fParam2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Constructs the MLP with the specified topology
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
/// <param name="fParam1">Free parameter α of the activation function</param>
/// <param name="fParam2">Free parameter β of the activation function</param>
#endif
public void Create(
Mat layerSizes,
MLPActivationFunc activFunc = MLPActivationFunc.SigmoidSym,
double fParam1 = 0, double fParam2 = 0)
{
if (disposed)
throw new ObjectDisposedException("StatModel");
if (layerSizes == null)
throw new ArgumentNullException("layerSizes");
layerSizes.ThrowIfDisposed();
NativeMethods.ml_CvANN_MLP_create_Mat(
ptr, layerSizes.CvPtr, (int)activFunc, fParam1, fParam2);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="layer_sizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activ_func">各ニューロンの活性化関数</param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="layer_sizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activ_func">Specifies the activation function for each neuron</param>
#endif
public CvANN_MLP(CvMat layer_sizes, MLPActivationFunc activ_func)
: this(layer_sizes, activ_func, 0, 0)
{
}
/// <summary>
/// 指定したトポロジーでMLPを構築する
/// </summary>
/// <param name="layer_sizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activ_func">各ニューロンの活性化関数</param>
/// <param name="f_param1">活性化関数のフリーパラメータα</param>
/// <param name="f_param2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Constructs the MLP with the specified topology
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
/// <param name="fParam1">Free parameter α of the activation function</param>
/// <param name="fParam2">Free parameter β of the activation function</param>
#endif
public void Create(CvMat layerSizes, MLPActivationFunc activFunc, Double fParam1, Double fParam2)
{
if (layerSizes == null)
throw new ArgumentNullException("layerSizes");
MLInvoke.CvANN_MLP_create(ptr, layerSizes.CvPtr, (int)activFunc, fParam1, fParam2);
}
/// <summary>
/// 指定したトポロジーでMLPを構築する
/// </summary>
/// <param name="layer_sizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activ_func">各ニューロンの活性化関数</param>
#else
/// <summary>
/// Constructs the MLP with the specified topology
/// </summary>
/// <param name="layerSizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activFunc">Specifies the activation function for each neuron</param>
#endif
public void Create(CvMat layerSizes, MLPActivationFunc activFunc)
{
Create( layerSizes, activFunc, 0, 0 );
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="layer_sizes">入出力層を含む各層のニューロン数を指定する整数のベクトル</param>
/// <param name="activ_func">各ニューロンの活性化関数</param>
/// <param name="f_param1">活性化関数のフリーパラメータα</param>
/// <param name="f_param2">活性化関数のフリーパラメータβ</param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="layer_sizes">The integer vector specifies the number of neurons in each layer including the input and output layers. </param>
/// <param name="activ_func">Specifies the activation function for each neuron</param>
/// <param name="f_param1">Free parameter α of the activation function</param>
/// <param name="f_param2">Free parameter β of the activation function</param>
#endif
public CvANN_MLP(CvMat layer_sizes, MLPActivationFunc activ_func, double f_param1, double f_param2)
{
if (layer_sizes == null)
throw new ArgumentNullException("layer_sizes");
this.ptr = MLInvoke.CvANN_MLP_construct_training(layer_sizes.CvPtr, (int)activ_func, f_param1, f_param2 );
base.NotifyMemoryPressure(SizeOf);
}