get_sample_class_gmmT_get_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm (算子)
名称
get_sample_class_gmmT_get_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm — 从高斯混合模型(GMM)的训练数据中返回训练样本。
签名
描述
get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm reads out a training sample from the
Gaussian Mixture Model (GMM) given by GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle that was
stored with add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm or
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm。The index of the sample is
specified with NumSampleNumSampleNumSampleNumSamplenumSamplenum_sample. The index is counted from 0,
i.e., NumSampleNumSampleNumSampleNumSamplenumSamplenum_sample must be a number between 0 and
NumSamplesNumSamplesNumSamplesNumSamplesnumSamplesnum_samples - 1, where NumSamplesNumSamplesNumSamplesNumSamplesnumSamplesnum_samples can be
determined with get_sample_num_class_gmmget_sample_num_class_gmmGetSampleNumClassGmmGetSampleNumClassGmmGetSampleNumClassGmmget_sample_num_class_gmm。The training
sample is returned in FeaturesFeaturesFeaturesFeaturesfeaturesfeatures and ClassIDClassIDClassIDClassIDclassIDclass_id.
FeaturesFeaturesFeaturesFeaturesfeaturesfeatures is a feature vector of length NumDimNumDimNumDimNumDimnumDimnum_dim,
while ClassIDClassIDClassIDClassIDclassIDclass_id is its class (see
add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm and create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm).
get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm can, for example, be used to reclassify
the training data with classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmClassifyClassGmmclassify_class_gmm in order to
determine which training samples, if any, are classified
incorrectly.
执行信息
- 多线程类型:可重入(与非独占算子并行运行)。
- 多线程作用域:全局(可从任何线程调用)。
- 未采用并行化处理。
参数
GMMHandleGMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (输入控制) class_gmm → HClassGmm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
GMM 句柄。
NumSampleNumSampleNumSampleNumSamplenumSamplenum_sample (输入控制) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Index of the stored training sample.
FeaturesFeaturesFeaturesFeaturesfeaturesfeatures (输出控制) real-array → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)
训练样本的特征向量。
ClassIDClassIDClassIDClassIDclassIDclass_id (输出控制) number → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
训练样本的类。
示例(HDevelop)
create_class_gmm (2, 2, [1,10], 'spherical', 'none', 2, 42, GMMHandle)
read_samples_class_gmm (GMMHandle, 'samples.gsf')
train_class_gmm (GMMHandle, 100, 1e-4, 'training', 1e-4, Centers, Iter)
* Reclassify the training samples
get_sample_num_class_gmm (GMMHandle, NumSamples)
for I := 0 to NumSamples-1 by 1
get_sample_class_gmm (GMMHandle, I, Features, Class)
classify_class_gmm (GMMHandle, Features, 2, ClassID, ClassProb,\
Density, KSigmaProb)
if (not (Class == ClassProb[0]))
* classified incorrectly
endif
endfor
结果
如果参数有效,算子
get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm 返回值 2 ( H_MSG_TRUE )。如有必要,则抛出异常。
可能的前趋
add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm,
add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm,
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmmread_samples_class_gmm,
get_sample_num_class_gmmget_sample_num_class_gmmGetSampleNumClassGmmGetSampleNumClassGmmGetSampleNumClassGmmget_sample_num_class_gmm
可能的后继
classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmClassifyClassGmmclassify_class_gmm,
evaluate_class_gmmevaluate_class_gmmEvaluateClassGmmEvaluateClassGmmEvaluateClassGmmevaluate_class_gmm
另见
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmmcreate_class_gmm
模块
基础