public static float train_epoch_quickprop_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb) { float ret = fannfloatPINVOKE.train_epoch_quickprop_parallel__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb); return ret; }
public static float train_epoch_quickprop_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb, floatVectorVector predicted_outputs) { float ret = fannfloatPINVOKE.train_epoch_quickprop_parallel__SWIG_1(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb, floatVectorVector.getCPtr(predicted_outputs)); if (fannfloatPINVOKE.SWIGPendingException.Pending) throw fannfloatPINVOKE.SWIGPendingException.Retrieve(); return ret; }
public static float train_epoch_incremental_mod(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, floatVectorVector predicted_outputs) { float ret = fannfloatPINVOKE.train_epoch_incremental_mod__SWIG_1(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), floatVectorVector.getCPtr(predicted_outputs)); if (fannfloatPINVOKE.SWIGPendingException.Pending) throw fannfloatPINVOKE.SWIGPendingException.Retrieve(); return ret; }
public static float train_epoch_incremental_mod(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data) { float ret = fannfloatPINVOKE.train_epoch_incremental_mod__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data)); return ret; }
public static float test_data_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb) { float ret = fanndoublePINVOKE.test_data_parallel__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb); return ret; }
public neural_net(SWIGTYPE_p_fann other) : this(fanndoublePINVOKE.new_neural_net__SWIG_7(SWIGTYPE_p_fann.getCPtr(other)), true) { }
public void copy_from_struct_fann(SWIGTYPE_p_fann other) { fanndoublePINVOKE.neural_net_copy_from_struct_fann(swigCPtr, SWIGTYPE_p_fann.getCPtr(other)); }