… (1)人工神经网络(artificial neural networks):生物神经网络是由… 中,同时使各类别内差别最小
.k-means聚类实现步骤:①在观测值中… k-means聚类算法适用于类内团聚状分布的样本数据 [14] .多…

… diagnosis using convolutional neural network combined with k-means clustering. … Machine
learning approaches for predicting hypertension and its associated factors using population-…

… 1􀆰 4 K-means聚类 K-means选用欧氏距离作为相似性度量ꎬ其 目标函数是最小化类内样本到聚类
中心… A comparison of intensive care unit mortality prediction models through the use of data …

… 由于传统的谱聚类算法中的分类算法还是K-means算法,因而需要预先指定聚类数目k;另外,谱聚
… for prediction of crude oil water content at wellhead metering based on CPN neural network[…

… for the diagnosis of heart conditions. For most people, … neural network，DNN）对S1 和
S2 进行分类，平均准确率为88.63%。Chen 等 [15] 先将心音转换为MFCC 的序列，然后使用K-means …

… ) 用于不平衡数据分类,采用K-means聚类方法进行欠采 样,选择使误… RUSBoost:a hybrid approach
to alleviating class imbalance[J… data classification method based on deep neural network …

… ]提出了 基于K-means 的过采样算法,该算法通过K-means 将少 … 了一 种基于K-means 的双边
采样方法,用K-means 方法分别 为… RUSBoost:a hybrid approach to alleviating class imbalance[J…

… A new automatic identifica⁃ tion method of heart failure using improved support vector machine
… A multi⁃task neural network architecture for renal dysfunction prediction in heart failure …

… 算法在划分粒的时候 采用的K-means聚类算法,即划分粒… prediction of chaotic time series
using a support vector machine[C]//Proceedings of the 1997 IEEE Workshop on Neural Networks …

… 摘要: 本文提出了一个基于多阶段聚类的深度神经网络(Deep Neural Network,DNN)预测模型
,… Support vector machine PM2.5 concentration prediction based on K-means clustering and …