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全部话题 - 话题: nnet
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w*******r
发帖数: 128
1
I know in R there is a package named nnet. Does someone know how to find
which function nnet uses to calculate the node output? Is it linear, RBF or
other functions? In addition, are there other good packages for neural
network beside nnet in R?
Thanks a lot!
w******a
发帖数: 25
2

e1071 only has one method called e1071.e1071-deprecated().
i don't know how to use it.
> e1071-deprecated()
Error: object 'e1071' not found

nnet
>train<-read.csv("dataset_nee.csv",header=T)
> nnet(x=train[,2:4],y=train[,5])
Error in nnet.default(x = train[, 2:4], y = train[, 5]) :
element 1 is empty;
the part of the args list of 'c' being evaluated was:
(size, dim(y)[2])
a**s
发帖数: 9606
3
nnets.com
a*f
发帖数: 1790
4
来自主题: Programming版 - 问几个神经网络的问题
一般实用的股票交易系统input layer的节点数量大概是什么规模(几百,几千还是更
多)?需要multilayers吗?training的数据量大致要多大?training算法有没有相对
比较好一点的选择?
http://www.mathworks.com/help/nnet/ug/choose-a-multilayer-neura
f***a
发帖数: 329
5
都有现成的package
neural network in R: library(nnet)
h***i
发帖数: 3844
6
nnet is good, I think

or
s*********e
发帖数: 1051
7
来自主题: Statistics版 - Does R have good neural network pacakges?
what's wrong with nnet package?
S******y
发帖数: 1123
8
naiveBayes - R package e1071
Neural Net - R package nnet
Collaborative Filtering (?) - Matlab??
d*******o
发帖数: 493
9
"统计是计算机最容易实现的部分". I don't think so.
Please find R's counterparts in Java:
rpart for decision tree;
randomForest for random forests;
nnet neural network;
e1071 or kernlab for support vector machines;
e1071 for Naive Bayes;
earth for multivariate adaptive regression splines;
RWeka for boosting
s*********e
发帖数: 1051
10
first of all, do not misuse the term "unbalanced".
secondly, if the event rate is too low, then the logistic regression won't
work anyway regardless of bagging or not. but in your case, 1/8 is not bad
at all.
thirdly, in case of extremely rare event, you should consider non-parametric
models such as tree-based / rule-based / nnet either directly or indirectly
with a 2-stage approach.
s*********e
发帖数: 1051
11
first of all, do not misuse the term "unbalanced".
secondly, if the event rate is too low, then the logistic regression won't
work anyway regardless of bagging or not. but in your case, 1/8 is not bad
at all.
thirdly, in case of extremely rare event, you should consider non-parametric
models such as tree-based / rule-based / nnet either directly or indirectly
with a 2-stage approach.
s********i
发帖数: 111
12
来自主题: Statistics版 - 问个简单的classification问题
呵呵,多谢,我也发现了,用了nnet里的multinom,不知为啥fit出来的都是直线,不
是应该用的MLE估算的linear fitting是logistic函数,再转换成概率的话应该是非线
性了吗?
l*****9
发帖数: 49
13
来自主题: DataSciences版 - Neural Network面试的时候会怎么问啊?
你好,你用什么软件包呢?pybrain?参数有这么详细吗?
用R中的neuralnet,nnet感觉内存很吃力。
自己编写我觉得要做好内存优化什么的很难啊。
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