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.
利用改進的模糊C均值算法對彩色圖像的顏色信息進行聚類,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均值聚類算法進行連續(xù)屬性模糊化,通過聚類有效性分析來確定最佳分類數(shù)目,克服了屬性模糊化方法需要人為確定劃分類數(shù)的缺點。
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)合了模糊c-均值聚類(FCM)算法和可能性c-均值聚類(PCM)算法優(yōu)點的聯(lián)合模糊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