Skip to main content

Questions tagged [nnet]

software for feed-forward neural networks and multinomial log-linear models.

Filter by
Sorted by
Tagged with
2 votes
0 answers
26 views

Can I use Multinomial Logistic Regression's probabilities as proxies for proportions?

Summary of the Problem: I am exploring methods to simultaneously predict the proportions of different tree species within 250 square meter forest plots using ALS (Airborne Laser Scanning) and spectral ...
candelas762's user avatar
0 votes
1 answer
53 views

Identical intercept and random effect values in multinomial regression model in R

I have 6 animals whose behaviour I’m testing over multiple trials. It’s a pretty small dataset (max 15 observations per animal). Behaviour falls into multiple types. The same behaviour can occur ...
anon's user avatar
  • 3
0 votes
0 answers
19 views

Multinomial regression with duplicated data points: aggregation or mixed effects?

I would like to run a multinomial model, and I would like feedback on how to deal with duplicates. Suppose the following example, which is quite close to my actual research question. I have data on a ...
M. Riera's user avatar
2 votes
1 answer
318 views

NNET Multinomial Regression - Error in looping through multiple independent variables and extracting coefficients/std.errors

I have a scenario in which I'm using multinom (from NNET package) to perform multinomial regression over a set of 100+ genes (a given gene is an independent variable in each multinomial regression). I ...
lm19246's user avatar
  • 23
1 vote
1 answer
437 views

Fitting a multinomial glm for a very large dataset

I have compositional data where for two groups, where each is represented by two ages, there are 100 possible categories for which I observed counts: ...
dan's user avatar
  • 333
1 vote
0 answers
330 views

Using a spatial tensor spline in a nnet:multinom multinomial fit in R

I know that in library(mgcv) one can use spatial tensor spline smooths in gam fits with a cyclical spline basis for longitude as ...
Tom Wenseleers's user avatar
1 vote
1 answer
266 views

Obtaining log-odds coefficients instead of proportions in output of post-hoc tests in emmeans package

I got in trouble for posting this on Stack Overflow a few days ago. It seemed to me more of a coding question than a statistical question (i.e. what argument to use in the ...
llewmills's user avatar
  • 2,043
1 vote
1 answer
105 views

Caret classifying above chance on randomly generated data

I am attempting to compare a few methods for multi-class classification using caret: 'multinom' (logistic regression), 'nnet' (neural net), and 'svmPoly' and 'svmLinear' (two types of support vector ...
Adam Morgan's user avatar
0 votes
1 answer
305 views

nnet package for OLS

First, I simulated some data according to the OLS condition: ...
user1329307's user avatar
1 vote
1 answer
208 views

Unreasonable bias when using nnet (R package caret) for time series forecasting

I have been trying to forecast a time series in a regression-like setting using neural networks (nnet method in R package caret)....
Sohrab's user avatar
  • 13
3 votes
1 answer
845 views

Emmeans produce negative values for prob 95%CI for multinomial regression

I'm fitting a multinomial logistic regression and I'm getting two issues: ...
Diego Pujoni's user avatar
3 votes
1 answer
2k views

Differences between multinomial models (mgcv and nnet)

I'm trying to understand the differences I see when applying multinomial logistic regression models in R using nnet and mgcv. For comparison purposes with glm() let's take only two levels for the ...
albifrons's user avatar
  • 133
0 votes
1 answer
334 views

¿Do i need to normalize/transform data in a multinomial (nnet:multinom) model? + Dropping variables by Likehood

So, im working with a dataset with controls and 4 diseases, its indeed a nested model cause they are 2 diseases with 2 level each, but i do not know well how to model it. The thing is i got over 40 ...
Galpaccru's user avatar
6 votes
1 answer
1k views

nnet::multinom confidence intervals extremely narrow, when mean of independent variable >> variance

I am using the package nnet to fit multinomial regression models using multinom(). When fitting the model using an independent ...
ndevln's user avatar
  • 353
3 votes
1 answer
1k views

Is it valid to use Anova (in R) to compare alternative multinomial log-linear models?

I am familiar with the idea of comparing alternative linear regression models using anova(model1,model2), for models fitted using ...
Izy's user avatar
  • 639
1 vote
1 answer
441 views

Interpreting R nnet Package Multinomial Regression

I need to interpret this summary. I have a response variable with 5 levels (response) and an explanatory variable (taxon) with 2 levels (raptor and others). Can someone help me? Call: ...
Natalia Rebolo's user avatar
3 votes
2 answers
4k views

Do I have to preprocess my new data for a prediction, if I have used preprocessing for building the model?

In this example preprocessing is used to construct a NN: ...
Marcel's user avatar
  • 99
1 vote
1 answer
3k views

How to select decay parameter in nnet R

I'm using the caret package's train function to optimize a neural net using nnet. I'm new to neuralnet modelling so this is a ...
Jon's user avatar
  • 141
1 vote
1 answer
2k views

which neural network to use?

I have explored this site for the answer but could not find what i was looking for. My problem is i have data containing many variables (22) that are continuos and categorical and my output has two ...
Martin's user avatar
  • 99
0 votes
1 answer
187 views

Which neural network package should i use?

I'm looking at running a neural network to predict the probability of a turtle becoming entangled in a fishing net. My input variables are fishing net characteristics that include continuos and ...
Martin's user avatar
  • 99
3 votes
0 answers
3k views

multinomial logistic regression with nnet package in R

I have recently realised that the way I thought the multinom function in nnet was running is not actually the way it is coded. I have looked high and low for information on how the models are ...
PeteKaz's user avatar
  • 31
2 votes
0 answers
3k views

Interpreting R nnet Package Multinomial Regression Model Summary

I was going over a multinomial regression example from Faraway, "Extending the Linear Model with R Generalized Linear, Mixed Effects and Nonparametric Regression Models", book. R script of the example ...
sen.a's user avatar
  • 21
2 votes
1 answer
3k views

How to deal with discrete and continuous output multi variables in neural network?

I have created neural networks using nnet for either discreate or continous output variables, but not using both at once. Now I have a problem in which the output ...
Eka's user avatar
  • 2,281
2 votes
0 answers
799 views

Case weights vs probability weights

I use functions in R as context for the question, but it is more generally about the meaning of two terms used to describe weights applied to cases in regression models. In lm, the "weights" argument ...
bsbk's user avatar
  • 1,197
2 votes
2 answers
2k views

Neural network becomes worse with more predictors

I am using a neural network with one layer of 20 hidden units (using the package nnet) for a classification problem where I have around 12 possible outcomes. I have around 4000 observations, and I am ...
mguzmann's user avatar
  • 665
2 votes
0 answers
154 views

Multinomial algorithm for probabilistic data

I am trying to predict the suffix a certain word will take based on properties of the word. There three outcomes but they are not absolute, that is, some words can take two or three different suffixes ...
mguzmann's user avatar
  • 665
0 votes
1 answer
3k views

R nnet (Caret) not giving results for size = 8 and above

This is my first post in CrossValidated hence please let me know if I may have inadvertently violated forum rules. I am working with nnet using Caret in R and when I am running experiments using the ...
Ian Lo's user avatar
  • 1
1 vote
1 answer
2k views

Multinomial logistic regression in R returns fewer categories

My dependent variable has 4 categories, but when I run the multinomial logistic regression using the package nnet with function ...
Nieve K's user avatar
  • 141
1 vote
0 answers
1k views

Multinomial logistic on grouped data with nnet package, R

This link from UCLA.edu (https://stats.idre.ucla.edu/r/dae/multinomial-logistic-regression/) provides a useful example for a multinomial logistic case. However, I wonder how can I correctly interpret ...
Valentin_Ștefan's user avatar
5 votes
0 answers
2k views

How to control the learning rate in R nnet? [closed]

I am dealing with the nnet package in R. I know that the momentum $\alpha$ is used to decrease the fluctuations in weight changes over consecutive iterations. The ...
Andrea Ianni's user avatar
2 votes
0 answers
158 views

Should I trust logistic regression in ABC model selection with more statistics than retained simulations?

I am using multinomial logistic regression to aid model selection in approximate Bayesian computation. However, I just realize at the preferred tolerance, the number of retained simulations is ...
ryhui's user avatar
  • 21
2 votes
2 answers
3k views

How do you turn the output of a nnet neural network model into an equation?

Assuming the output of the above nnet feedforward model (nnetModel) is such that the following summary is produced: ...
dts86's user avatar
  • 689
0 votes
1 answer
2k views

Which data transformation can improve the performance of MLP neural networks for classification?

I am trying to fit several MLP neural networks models with a single hidden layer using the caret R-package. My main concern now is in the preprocessing step. My train data features (16 in total) are ...
Alejandro CC's user avatar
1 vote
0 answers
708 views

How can I solve this classification problem?

I working with R on a classification problem. My outcome variable is binary with two levels 1 and 2. First of all I tried the logistic regression, which of all methods has the best performance, ...
Charlotte's user avatar
  • 405
3 votes
1 answer
2k views

What is the "value of fitting criterion" on the nnet package in R?

When you run the function nnet of the nnet package a sequence of values is shown on the console like this (made up numbers): initial value 100 iter 10 value 88 iter 20 value 80 final value 60 And ...
Makondo's user avatar
  • 211
2 votes
1 answer
9k views

r - choosing correct nnet model

Language: R Background data = 1800 observations (rows) x 5 variables (columns) I am using library(caret) and training regression models using ...
tospig's user avatar
  • 165
7 votes
3 answers
8k views

(Feed-Forward) Neural Networks keep converging to mean

I'm having an interesting dilemma with the neuralnet and nnet packages in R. I recently ...
gtnbz2nyt's user avatar
  • 225
3 votes
2 answers
5k views

Training nnet and avNNet models with caret when the output has negatives

My question is about the typical feed-forward single-hidden-layer backprop neural network, as implemented in package nnet, and trained with 'train()' in package caret. This is related to this question ...
bsbk's user avatar
  • 1,197
1 vote
0 answers
2k views

Calculate prediction error for a multinomial output like in the "effects" package

After fitting a multinomial model to my data with the "multinom" function (package nnet), I want to show the effect of selected variables controlling for other variable values. I know that the "...
Arnaud's user avatar
  • 243
2 votes
0 answers
289 views

How to Obtain “Right” Parameters of Multinomial Logit Model (or Other Conditional Models) in R?

I started to use the function multinom of R package nnet in order to fit several conditional ...
Pippo's user avatar
  • 647
4 votes
1 answer
3k views

Neural network for prediction

I am working on neural networks for a regression problem in R using packages like nnet, caret etc. I have split my data into ...
NG_21's user avatar
  • 1,556
8 votes
1 answer
4k views

What's the activation function used in the nodes of hidden layer from nnet library in R?

Most references I find say that the activation function used in nnet is 'usually' a logistic function. But in the case that I would like to test the performance of ...
user35549's user avatar
9 votes
2 answers
35k views

Example of time series prediction using neural networks in R

Anyone's got a quick short educational example how to use neural networks (nnet in R for example) for the purpose of prediction? Here is an example, in R, of a ...
dfhgfh's user avatar
  • 399
15 votes
1 answer
26k views

How to deal with a mix of binary and continuous inputs in neural networks? [duplicate]

I'm using the nnet package in R to attempt to build an ANN to predict real estate prices for condos (personal project). I am new to this and don't have a math background so please bare with me. I ...
ChrisArmstrong's user avatar