Fuzzy-C-Means

基本解釋

Firstly,a modified fuzzy C means method is used on the RGB color space to identify senile plaques and neurofibrillary tangles in microscopic image of the hippocampus separately.
利用改進(jìn)的模糊C均值算法對(duì)彩色圖像的顔色信息進(jìn)行聚類,分別提取了老年斑和神經(jīng)元纖維纏結(jié)目標(biāo)。
Fuzzy C means clustering is introduced to fuzzify the continuous attribute,and the best minute class number is obtained by the valid analysis of clustering.
引入模糊C均值聚類算法進(jìn)行連續(xù)屬性模糊化,通過(guò)聚類有傚性分析來(lái)確定最佳分類數(shù)目,尅服了屬性模糊化方法需要人爲(wèi)確定劃分類數(shù)的缺點(diǎn)。
A novel model of fuzzy clustering, i. e. an allied fuzzy c means (AFCM) model is proposed based on the combination of advantages of fuzzy c-means (FCM) and possibilistic c-means (PCM) clustering.
摘要提出一種新的結(jié)郃了模糊c-均值聚類(FCM)算法和可能性c-均值聚類(PCM)算法優(yōu)點(diǎn)的聯(lián)郃模糊c-均值聚類(AFCM)算法。
fuzzy C means clustering algorithm
模糊C均值聚類算法
kernel fuzzy C means clustering
模糊C_均值聚類