/// <summary>
///
/// </summary>
/// <param name="fs"></param>
/// <param name="node"></param>
/// <param name="forest"></param>
/// <param name="data"></param>
#else
/// <summary>
///
/// </summary>
/// <param name="fs"></param>
/// <param name="node"></param>
/// <param name="forest"></param>
/// <param name="data"></param>
#endif
public virtual void Read(CvFileStorage fs, CvFileNode node, CvRTrees forest, CvDTreeTrainData data)
{
if (fs == null)
throw new ArgumentNullException("fs");
if (node == null)
throw new ArgumentNullException("node");
if (forest == null)
throw new ArgumentNullException("forest");
if (data == null)
throw new ArgumentNullException("data");
MLInvoke.CvForestTree_read(ptr, fs.CvPtr, node.CvPtr, forest.CvPtr, data.CvPtr);
}
/// <summary>
///
/// </summary>
/// <param name="train_data"></param>
/// <param name="subsample_idx"></param>
/// <param name="forest"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="subsampleIdx"></param>
/// <param name="forest"></param>
/// <returns></returns>
#endif
public virtual bool Train( CvDTreeTrainData trainData, CvMat subsampleIdx, CvRTrees forest )
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (subsampleIdx == null)
throw new ArgumentNullException("subsampleIdx");
if (forest == null)
throw new ArgumentNullException("forest");
return MLInvoke.CvForestTree_train(ptr, trainData.CvPtr, subsampleIdx.CvPtr, forest.CvPtr);
}
/// <summary>
/// 決定木を学習する
/// </summary>
/// <param name="train_data"></param>
/// <param name="subsample_idx"></param>
/// <param name="ensemble"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains decision tree
/// </summary>
/// <param name="trainData"></param>
/// <param name="subsampleIdx"></param>
/// <param name="ensemble"></param>
/// <returns></returns>
#endif
public virtual bool Train(CvDTreeTrainData trainData, CvMat subsampleIdx, CvBoost ensemble)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (subsampleIdx == null)
throw new ArgumentNullException("subsampleIdx");
IntPtr ensemblePtr = (ensemble == null) ? IntPtr.Zero : ensemble.CvPtr;
return MLInvoke.CvBoostTree_train(ptr, trainData.CvPtr, subsampleIdx.CvPtr, ensemblePtr);
}
/// <summary>
///
/// </summary>
/// <param name="fs"></param>
/// <param name="node"></param>
/// <param name="ensemble"></param>
/// <param name="data"></param>
#else
/// <summary>
///
/// </summary>
/// <param name="fs"></param>
/// <param name="node"></param>
/// <param name="ensemble"></param>
/// <param name="data"></param>
#endif
public virtual void Read(CvFileStorage fs, CvFileNode node, CvBoost ensemble, CvDTreeTrainData data)
{
if (fs == null)
throw new ArgumentNullException("fs");
if (node == null)
throw new ArgumentNullException("node");
if (ensemble == null)
throw new ArgumentNullException("ensemble");
if (data == null)
throw new ArgumentNullException("data");
MLInvoke.CvBoostTree_read(ptr, fs.CvPtr, node.CvPtr, ensemble.CvPtr, data.CvPtr);
}
/// <summary>
/// 決定木を学習する
/// </summary>
/// <param name="train_data"></param>
/// <param name="subsample_idx"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains decision tree
/// </summary>
/// <param name="trainData"></param>
/// <param name="subsampleIdx"></param>
/// <returns></returns>
#endif
public virtual bool Train(CvDTreeTrainData trainData, CvMat subsampleIdx)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
IntPtr subsampleIdxPtr = (subsampleIdx == null) ? IntPtr.Zero : subsampleIdx.CvPtr;
return MLInvoke.CvDTree_train(ptr, trainData.CvPtr, subsampleIdxPtr);
}
