maNormNN(nnNorm)
maNormNN()所属R语言包：nnNorm
Intensity and spatial normalization using robust neural networks fitting
使用强大的拟合神经网络的强度和空间标准化
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function normalizes a batch of cDNA arrays by removing the intensity and spatial dependent bias.
此功能标准化一批cDNA阵列通过删除强度和空间依赖偏见。
用法----------Usage----------
maNormNN(mbatch,w=NULL,binWidth=3,binHeight=3,model.nonlins=3,iterations=100,nFolds=10,maplots=FALSE,verbose=FALSE)
参数----------Arguments----------
参数：mbatch
A marrayRaw or marrayNorm batch of arrays.
一个marrayRaw或marrayNorm一批阵列。
参数：w
Weights to be assigned to each spot. If provided, it should be a vector with the same length as maNspots(mbatch).
被分配到每个点的权重。如果提供的话，它应该是一个与为maNspots（mbatch）相同长度的向量。
参数：binWidth
Width of the bins in the X direction (spot column) in which the print tip will be divided in order to account for spatial variation. Max value is maNsc(mbatch), Min value is 1. However if it is set to a number larger than maNsc(mbatch)/2 (so less than two bins in X direction) the variable X will not be used as predictor to estimate the bias.
宽度X方向箱（现货列）打印头将被划分在空间变异帐户。最大值maNsc(mbatch)，最小值为1。然而，如果它被设置为一个数字maNsc(mbatch)/2（不到两个垃圾桶在X方向）变量X不会被用来作为预测估计偏差较大。
参数：binHeight
Height of the bins in the Y direction (spot row)in which the print tip will be divided in order to account for spatial variation. Max value is maNsr(mbatch), Min value is 1. However if it is set to a number larger than maNsr(mbatch)/2 (so less than two bins in Y direction) the variable Y will not be used as predictor to estimate the bias.
高度Y方向（点行）打印头将被划分在空间变异帐户箱。最大值maNsr(mbatch)，最小值为1。然而，如果它被设置为一个数字maNsr(mbatch)/2（不到两个垃圾桶在Y方向）变量Y不会被用来作为预测估计偏差较大。
参数：model.nonlins
Number of nodes in the hidden layer of the neural network model.
在神经网络模型的隐层节点的数目。
参数：iterations
The number of iterations at which (if not converged) the training of the neural net will be stopped.
（如果不是融合）将停止迭代神经网络的训练。
参数：nFolds
Number of cross-validation folds. It represents the number of equal parts in which the data from a print tip is divided into: the model is trained on nFolds-1 parts and the bias is estimated for one part at the time. Higher values improve the results but increase the computation time. Ideal values are between 5 and 10.
交叉验证褶皱。它代表的从打印头的数据被分成若干等份nFolds-1部分：模型训练和偏见是一个时间估计。更高的价值提高的结果，但增加了计算时间。理想值是5和10之间。
参数：maplots
If set to "TRUE" will produce a M-A plot for each slide before and after normalization.
如果设置"TRUE"标准化之前和之后会产生一个M-A每张幻灯片的图。
参数：verbose
If set to "TRUE" will show the output of the nnet function which is training the neural network models.
如果设置为"TRUE"将显示的nnet功能，这是训练神经网络模型的输出。
Details
详情----------Details----------
This function uses neural networks to model the bias in cDNA data sets.
此功能使用神经网络模型中的基因数据集的偏见。
值----------Value----------
A marrayNorm object containing the normalized log ratios. See marrayNorm class for details
一个marrayNorm对象，其中包含归log比率。看到marrayNorm类
作者（S）----------Author(s)----------
Tarca, A.L.
参考文献----------References----------
intensity dependent normalization of cDNA data. Bioinformatics. 2004,submitted.<br>
参见----------See Also----------
compNorm,nnet
compNorm，nnet
举例----------Examples----------
# Normalization of swirl data[标准化的漩涡数据]
data(swirl)
# print-tip, intensity and spatial normalization of the first slide in swirl data set[打印头，强度和空间标准化的漩涡数据集的第一张幻灯片]
swirlNN<-maNormNN(swirl[,1])
#do not consider spatial variations, and display M-A plots before and after normalization[不考虑标准化之前和之后的时空变化，并显示主图]
swirlNN<-maNormNN(swirl[,1],binWidth=maNsc(swirl),binHeight=maNsr(swirl),maplots=TRUE)
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-26 07:49:52
