/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <returns></returns>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <returns></returns>
#endif
public CvDTreeTrainData(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx = null,
CvMat sampleIdx = null,
CvMat varType = null,
CvMat missingMask = null,
CvDTreeParams param = null,
bool shared = false,
bool addLabels = false)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if(param == null)
param = new CvDTreeParams();
ptr = NativeMethods.ml_CvDTreeTrainData_new2(
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr,
shared ? 1 : 0,
addLabels ? 1 : 0
);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
#endif
public CvBoost(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx = null,
CvMat sampleIdx = null,
CvMat varType = null,
CvMat missingMask = null,
CvBoostParams param = null)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
param = new CvBoostParams();
ptr = NativeMethods.ml_CvBoost_new_CvMat(
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr
);
}
/// <summary>
/// ランダムツリーモデルの学習
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains Random Trees model
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#endif
public virtual bool Train(
Mat trainData,
DTreeDataLayout tflag,
Mat responses,
Mat varIdx = null,
Mat sampleIdx = null,
Mat varType = null,
Mat missingMask = null,
CvRTParams param = null)
{
if (trainData == null)
{
throw new ArgumentNullException("trainData");
}
if (responses == null)
{
throw new ArgumentNullException("responses");
}
if (param == null)
{
param = new CvRTParams();
}
return(NativeMethods.ml_CvRTrees_train_CvMat(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr) != 0);
}
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <param name="updateData"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <param name="updateData"></param>
/// <returns></returns>
#endif
public void SetData(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx = null,
CvMat sampleIdx = null,
CvMat varType = null,
CvMat missingMask = null,
CvDTreeParams param = null,
bool shared = false,
bool addLabels = false,
bool updateData = false)
{
if (trainData == null)
{
throw new ArgumentNullException(nameof(trainData));
}
if (responses == null)
{
throw new ArgumentNullException(nameof(responses));
}
if (param == null)
{
param = new CvDTreeParams();
}
NativeMethods.ml_CvDTreeTrainData_set_data(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr,
shared ? 1 : 0,
addLabels ? 1 : 0,
updateData ? 1 : 0
);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <returns></returns>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <returns></returns>
#endif
public CvDTreeTrainData(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx = null,
CvMat sampleIdx = null,
CvMat varType = null,
CvMat missingMask = null,
CvDTreeParams param = null,
bool shared = false,
bool addLabels = false)
{
if (trainData == null)
{
throw new ArgumentNullException("trainData");
}
if (responses == null)
{
throw new ArgumentNullException("responses");
}
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
{
param = new CvDTreeParams();
}
ptr = NativeMethods.ml_CvDTreeTrainData_new2(
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr,
shared ? 1 : 0,
addLabels ? 1 : 0
);
}
/// <summary>
/// ブーストされた分類器の学習
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="update"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains boosted tree classifier
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="update"></param>
/// <returns></returns>
#endif
public virtual bool Train(
Mat trainData,
DTreeDataLayout tflag,
Mat responses,
Mat varIdx = null,
Mat sampleIdx = null,
Mat varType = null,
Mat missingMask = null,
CvBoostParams param = null,
bool update = false)
{
if (trainData == null)
{
throw new ArgumentNullException("trainData");
}
if (responses == null)
{
throw new ArgumentNullException("responses");
}
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
{
param = new CvBoostParams();
}
int ret = NativeMethods.ml_CvBoost_train_Mat(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr,
update ? 1 : 0);
return(ret != 0);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
#endif
public CvBoost(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx = null,
CvMat sampleIdx = null,
CvMat varType = null,
CvMat missingMask = null,
CvBoostParams param = null)
{
if (trainData == null)
{
throw new ArgumentNullException("trainData");
}
if (responses == null)
{
throw new ArgumentNullException("responses");
}
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
{
param = new CvBoostParams();
}
ptr = NativeMethods.ml_CvBoost_new_CvMat(
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr
);
}
/// <summary>
/// 決定木を学習する
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains decision tree
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#endif
public virtual bool Train(
Mat trainData,
DTreeDataLayout tflag,
Mat responses,
Mat varIdx,
Mat sampleIdx,
Mat varType,
Mat missingMask,
CvDTreeParams param)
{
if (trainData == null)
{
throw new ArgumentNullException(nameof(trainData));
}
if (responses == null)
{
throw new ArgumentNullException(nameof(responses));
}
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
{
param = new CvDTreeParams();
}
return(NativeMethods.ml_CvDTree_train_Mat(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr) != 0);
}
/// <summary>
/// ブーストされた分類器の学習
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_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 boosted tree classifier
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></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 varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask,
CvBoostParams @params )
{
return Train(trainData, tflag, responses, varIdx, sampleIdx, varType, missingMask, @params, false);
}
/// <summary>
/// ブーストされた分類器の学習
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains boosted tree classifier
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <returns></returns>
#endif
public virtual bool Train(CvMat trainData, DTreeDataLayout tflag, CvMat responses)
{
return Train(trainData, tflag, responses, null, null, null, null, new CvBoostParams(), false);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
/// <param name="params"></param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="params"></param>
#endif
public CvBoost(CvMat trainData, DTreeDataLayout tflag, CvMat responses,
CvMat varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask, CvBoostParams @params )
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
if(@params == null)
@params = new CvBoostParams();
IntPtr varIdxPtr = (varIdx == null) ? IntPtr.Zero : varIdx.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;
ptr = MLInvoke.CvBoost_construct_training(
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
varIdxPtr,
sampleIdxPtr,
varTypePtr,
missingMaskPtr,
@params.CvPtr
);
NotifyMemoryPressure(SizeOf);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
#endif
public CvBoost(CvMat trainData, DTreeDataLayout tflag, CvMat responses,
CvMat varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask )
: this(trainData, tflag, responses, varIdx, sampleIdx, varType, missingMask, new CvBoostParams())
{
}
/// <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>
/// <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>
/// <returns></returns>
#endif
public virtual bool Train(CvMat trainData, DTreeDataLayout tflag, CvMat responses,
CvMat compIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask)
{
return Train(trainData, tflag, responses, compIdx, sampleIdx, varType, missingMask, new CvRTParams());
}
/// <summary>
/// ランダムツリーモデルの学習
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains Random Trees model
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#endif
public virtual bool Train(
Mat trainData,
DTreeDataLayout tflag,
Mat responses,
Mat varIdx = null,
Mat sampleIdx = null,
Mat varType = null,
Mat missingMask = null,
CvRTParams param = null)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
if (param == null)
param = new CvRTParams();
return NativeMethods.ml_CvRTrees_train_CvMat(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr) != 0;
}
/// <summary>
///
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <returns></returns>
#endif
public void SetData(CvMat trainData, DTreeDataLayout tflag, CvMat responses)
{
SetData(trainData, tflag, responses, null, null, null, null, new CvDTreeParams(), false, false, false);
}
/// <summary>
/// ブーストされた分類器の学習
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
/// <param name="params"></param>
/// <param name="update"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains boosted tree classifier
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="params"></param>
/// <param name="update"></param>
/// <returns></returns>
#endif
public virtual bool Train(CvMat trainData, DTreeDataLayout tflag, CvMat responses,
CvMat varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask,
CvBoostParams @params, Boolean update )
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
if(@params == null)
@params = new CvBoostParams();
IntPtr varIdxPtr = (varIdx == null) ? IntPtr.Zero : varIdx.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.CvBoost_train(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
varIdxPtr,
sampleIdxPtr,
varTypePtr,
missingMaskPtr,
@params.CvPtr,
update
);
}
/// <summary>
///
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <returns></returns>
#endif
public void SetData(CvMat trainData, DTreeDataLayout tflag, CvMat responses, CvMat varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask)
{
SetData(trainData, tflag, responses, varIdx, sampleIdx, varType, missingMask, new CvDTreeParams(), false, false, false);
}
/// <summary>
/// ブーストされた分類器の学習
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="update"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains boosted tree classifier
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <param name="update"></param>
/// <returns></returns>
#endif
public virtual bool Train(
Mat trainData,
DTreeDataLayout tflag,
Mat responses,
Mat varIdx = null,
Mat sampleIdx = null,
Mat varType = null,
Mat missingMask = null,
CvBoostParams param = null,
bool update = false)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if (param == null)
param = new CvBoostParams();
int ret = NativeMethods.ml_CvBoost_train_Mat(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr,
update ? 1 : 0);
return ret != 0;
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <returns></returns>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <returns></returns>
#endif
public CvDTreeTrainData(CvMat trainData, DTreeDataLayout tflag, CvMat responses, CvMat varIdx)
: this(trainData, tflag, responses, varIdx, null, null, null, new CvDTreeParams(), false, false)
{
}
/// <summary>
///
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="var_idx"></param>
/// <param name="sample_idx"></param>
/// <param name="var_type"></param>
/// <param name="missing_mask"></param>
/// <param name="params"></param>
/// <param name="shared"></param>
/// <param name="add_labels"></param>
/// <param name="update_data"></param>
/// <returns></returns>
#else
/// <summary>
///
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="params"></param>
/// <param name="shared"></param>
/// <param name="addLabels"></param>
/// <param name="updateData"></param>
/// <returns></returns>
#endif
public void SetData(CvMat trainData, DTreeDataLayout tflag, CvMat responses, CvMat varIdx, CvMat sampleIdx, CvMat varType, CvMat missingMask,
CvDTreeParams @params, bool shared, bool addLabels, bool updateData)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
if(@params == null)
@params = new CvDTreeParams();
IntPtr varIdxPtr = (varIdx == null) ? IntPtr.Zero : varIdx.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;
MLInvoke.CvDTreeTrainData_set_data(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
varIdxPtr,
sampleIdxPtr,
varTypePtr,
missingMaskPtr,
@params.CvPtr,
shared, addLabels, updateData
);
}
/// <summary>
/// 学習データを与えて初期化
/// </summary>
/// <param name="train_data"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
#else
/// <summary>
/// Training constructor
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
#endif
public CvBoost(CvMat trainData, DTreeDataLayout tflag, CvMat responses)
: this(trainData, tflag, responses, null, null, null, null, new CvBoostParams())
{
}
/// <summary>
/// 決定木を学習する
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#else
/// <summary>
/// Trains decision tree
/// </summary>
/// <param name="trainData"></param>
/// <param name="tflag"></param>
/// <param name="responses"></param>
/// <param name="varIdx"></param>
/// <param name="sampleIdx"></param>
/// <param name="varType"></param>
/// <param name="missingMask"></param>
/// <param name="param"></param>
/// <returns></returns>
#endif
public virtual bool Train(
CvMat trainData,
DTreeDataLayout tflag,
CvMat responses,
CvMat varIdx,
CvMat sampleIdx,
CvMat varType,
CvMat missingMask,
CvDTreeParams param)
{
if (trainData == null)
throw new ArgumentNullException("trainData");
if (responses == null)
throw new ArgumentNullException("responses");
trainData.ThrowIfDisposed();
responses.ThrowIfDisposed();
if(param == null)
param = new CvDTreeParams();
return NativeMethods.ml_CvDTree_train1(
ptr,
trainData.CvPtr,
(int)tflag,
responses.CvPtr,
Cv2.ToPtr(varIdx),
Cv2.ToPtr(sampleIdx),
Cv2.ToPtr(varType),
Cv2.ToPtr(missingMask),
param.CvPtr) != 0;
}