JIES THAM - 交通大學電機資訊國際學位學程學位論文, 2016 - airitilibrary.com
… method consists of two different recognition techniques, 1) the histogram dissimilarity measurement with K-Nearest-Neighbour … feature with statistical approachclassification. Because …
… : knearestneighbor (kNN) basedmethod, instead of ignoring missing observations to make data incomplete. KNN based … We compare the novel imputation techniques with mean …
… (αi,βi,gij,hij) from experimental timeseries data of gene expression. … neighboralgorithm, we obtained the so-called knearest … [13] as a nonparametric feature pre-selection method. In this …
YK Chen, WM Xiao, D Wang, L Shi… - 中国神经再生研究 …, 2013 - sjzsyj.com.cn
… Tissue classification was performed using the supervised k-nearestneighbor classifier for … of infarcts and volume of white matter lesions were determined as non-parametric data. …
… , with k-nearestneighbor consensus and Wang method, using 80% … To generate timeseries data and determine the temporal … level) was evaluated based on non-parametric Shannon’s …
… In contrast, k-nearestneighbor (k-NN) models are non-parametricclassification algorithms that … Researchers intend to develop DL classification models based on timeseries to learn …
… Instead of using raw timeseries data, we used wavelet … The algorithm calculates the k-nearest neighbors and … In this section, we used a non-parametric wavelet approach instead of a …
… methods are classified into parametric and non-parametric … 预测的多层k-NN(multilayer k-nearestneighbor,简称Mk-NN)框架[… Combining kohonen maps with arima timeseries models to …
… This study used the technique of Non-parametric Nonuniform intensity … the knearestneighbor (kNN) search method (k=9) as the classifier. To fairly evaluate the accuracy of classification, …