/// <summary>
/// ランダムツリーモデルの学習
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="comp_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
/// <param name="params"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains Random Trees model
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="compIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="params"></param>
/// <returns></returns>
#endif
public virtual bool Train(CvMat trainData, DTreeDataLayout tflag, CvMat responses,
CvMat compIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask, CvRTParams @params)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
if(@params == null)
@params = new CvRTParams();
IntPtr compIdxPtr = (compIdx == null) ? IntPtr.Zero : compIdx.CvPtr;
IntPtr sampleIdxPtr = (sampleIdx == null) ? IntPtr.Zero : sampleIdx.CvPtr;
IntPtr varTypePtr = (varType == null) ? IntPtr.Zero : varType.CvPtr;
IntPtr missingMaskPtr = (missingMask == null) ? IntPtr.Zero : missingMask.CvPtr;
return MLInvoke.CvRTrees_train(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
compIdxPtr, sampleIdxPtr, varTypePtr, missingMaskPtr,
@params.CvPtr
);
}
/// <summary>
///
/// </summary>
/// <param name="data"></param>
/// <param name="params"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="data"></param>
/// <param name="params"></param>
/// <returns></returns>
#endif
public bool Train(CvMLData data, CvRTParams @params)
{
if (data == null)
throw new ArgumentNullException("data");
if (@params == null)
@params = new CvRTParams();
return MLInvoke.CvERTrees_train2(ptr, data.CvPtr, @params.CvPtr);
}
