1.create_class_gmm — Create a Gaussian Mixture Model for classification 创建一个高斯混合模型分类器create_class_gmm( : : NumDim, NumClasses, NumCenters, CovarType, Preprocessing, NumComponents, RandSeed : GMMHandle)*NumDim 数据维数,如2D图像数据为2*NumClasses 分类器分类种数...
Heck LP, Chou KC (1994) Gaussian mixture model classifier for machine monitoring. Proceedings of the IEEE world Congress on Computational Neural Network and International Conference on Intelligence 7:4493–4496Heck L. P., Chou K. C., Gaussian mixture model classifiers for machine monitoring, ...
Therefore, if only a traditional classifier is used to classify the data, the final classification effect will be affected. To improve the classification of the credit data sets, a Gaussian mixture model based combined resampling algorithm is proposed. This resampling approach first determines the ...
About this paper Cite this paper de Melo, A.C.O., de Moraes, R.M., dos Santos Machado, L. (2003). Gaussian Mixture Models for Supervised Classification of Remote Sensing Multispectral Images. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds) Progress in Pattern Recognition, Speech and Ima...
After each classifier has been tuned to their best configuration, they are also fused together in different ways. In the end, the performances of the two classifiers are compared to each other and to the performances of their fusions. The fusion method where the scores of the classifiers are ...
#Since we have class labels for the training data, we can#initialize the GMM parameters in a supervised manner.classifier.means_ = np.array([X_train[y_train == i].mean(axis=0)foriinxrange(n_classes)])#axis=0 沿着Matrix的‘行’求统计量,NB:每个向量的第一元素求mean,第二个元素求mean...
Relan et al (Relan et al., 2013). employed the GMM-EM (Gaussian mixture model, expectation maximization) unsupervised classifier and a quadrant pairing method based on color features to automatically classifyretinal vessels. In their recent work (Relan and Relan, 2021), they expanded on this...
The discriminative splitting idea is employed for Gaussian mixture densities followed by learning via the introduced method. Then, the GMM classifier was applied to distinguish between healthy infants and those that present a selected set of medical conditions. Each group includes both full-term and ...
I present an alternative approach to classifying participant responses on the interrupted search task by fitting a Gaussian mixture model to response distributions. The parameter estimates obtained from fitting this model can then be used in a naïve Bayesian classifier to allow for probabilistic clas...
摘要: This paper proposes the use of Gaussian Mixture Models as a supervised classifier for remote sensing multispectral images. The main advantage of this approach is provide more adequated adjust to...DOI: 10.1007/978-3-540-24586-5_54 被引量: 22 ...