1) Supervised learning classification
有监督学习分类
2) supervised learning
有监督学习
1.
A Method of Choosing Web Services based on Supervised Learning Principle;
一种基于有监督学习原理的Web服务选择方法
2.
By using optimal cluster algorithm in combination with supervised learning of training system, functional approximation efficiency is improved.
本文依据可加性模糊系统理论 ,提出了一种新的预测方法 ,利用聚类方法与有监督学习相结合的训练方法 ,提高了系统的函数逼近能力。
3) Supervised classification
有监督分类
1.
This paper is from the angle of pattern recognition,have expounded Fuzzy to synthesize judge is a kind of important teaching method that realization has supervised classification in pattern recognition,it is also the effective means that application manages in college teacher teaching quality ration.
从模式识别角度,阐明了Fuzzy综合评判是模式识别中实现有监督分类的一种重要教学方法,亦是应用于高校教师教学质量定量管理的有效手段。
4) learning method with supervision
有监督式学习
1.
It utilized the characteristic that neural network can approach nonlinear function with arbitrary precision,adopted neural network s learning method with supervision,and regarded the prediction error as feedback to adjust the weighted values in flood level prediction network in order to achieve the objective of study.
利用神经网络能以任意精度逼近非线性函数的特点,采用神经网络的有监督式学习,并将预测误差作为反馈来调整水位预测网络中的权值分布,以达到学习的目的。
5) supervised texture classification
有监督纹理分类
6) supervised learning
监督学习
1.
Land evaluation based on agglomerative hierarchical cluster algorithm combining with supervised learning algorithm;
融合监督学习与凝聚层次聚类的土地评价方法
2.
Aimed at the problem of electroencephalography(EEG) pattern recognition in brain computer interfaces(BCIs),a classification method based on probabilistic neural network(PNN) with supervised learning was presented.
针对脑机接口(BCI)研究中脑电信号(EEG)的模式识别问题,提出了一种基于有监督学习的概率神经网络(PNN)的分类方法。
3.
The learning of connectionism,which consists mainly of supervised learning,intensive learning and unsupervised learning,is modelled after the learning of human beings.
其学习是对人类学习的模拟,主要有监督学习、强化学习和无监督学习三种。
补充资料：有监督学习
分子式：
CAS号：
性质：用已知某种或某些特性的样本作为训练集，以建立一个数学模型(如模式识别中的判别模型，人工神经网络法中的权重模型等)，再用已建立的模型来预测未知样本，此种方法称为有监督学习。
CAS号：
性质：用已知某种或某些特性的样本作为训练集，以建立一个数学模型(如模式识别中的判别模型，人工神经网络法中的权重模型等)，再用已建立的模型来预测未知样本，此种方法称为有监督学习。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条