1
vote
0answers
40 views

R AUC never less than 0.5?

I'm doing some work with random forests in R using the randomForest package, and I've run into something that seems odd to me. Even when the data is completely ...
0
votes
3answers
113 views

using random forest for missing data imputation in categorical variables ( in R)

I have following type of associated data. The following example step to generate associated variable. p number of variables and n is number of observations. ...
0
votes
1answer
33 views

randomSurvivalForest in R

I'm using the randomSurvivalForest package for R, version 3.6.4. I have been using it for a project for a while, with no problem. However, now I have added some additional predictors to my dataset, ...
5
votes
1answer
87 views

Random Forest checklist

I am building a random forest model in R. Based on my research I (hope to) have come up with quite some understanding about how they work, and more importantly when they work. I simply would like to ...
3
votes
0answers
37 views

Random Forest - how to know if variables affect positively or negatively

I'm running a RandomForest in R on a set of data with many variables. Using varImpPlot() I know how important is each variable ...
1
vote
0answers
33 views

RandomForest: how to use a person_id and company_id attribute in machine learning

I'm trying to train a randomForest model in R in a 500k+ row dataset. So far so good, but now I'm trying to include factors person_id and company_id (non-unique) which both have a huge amount of ...
2
votes
0answers
38 views

How can I include random effects into a randomForest

I'm not even sure that the question makes much sense, but I think I saw a couple of titles of papers where they proposed random forest with random effects. Is this possible in R?
1
vote
0answers
28 views

Random Forest regression model in R and data overfitting

I have trained my random forest model on a 74,000 training examples where each example consists of two proteins Amino Acids sequence (20 characters) and some numeric values representing the similarity ...
1
vote
1answer
58 views

Is random forest applied only to continuous response variable?

I am trying to apply random forest on a binary response variable, but it's saying the response variable has 5 or fewer unique values. Was it happening because random forest works only with the ...
0
votes
0answers
52 views

applying random forest in place of decision tree method in R

I am relatively new to random forest technique. I applied decision tree successfully to a data predicting 1/0 outcome. The predictors are mixture of continuous and categorical. I was trying similar ...
0
votes
0answers
23 views

Dropping predictor variables, based on variable of importance, effect of Random Forest Accuracy

I am trying to use Random Forest to accurately predict forested land cover classes using Landsat 7, climatic and geographical data. I have 23 predictor variables and 1 response variable. When I drop ...
0
votes
0answers
10 views

mtry values versus OOBE chart analysis

I was working on a dataset of 100,000 cases and 200 variables, and ran 7 different mtry values, trying to find the optimal one. Using the same data and same ntree values, I compared the different ...
0
votes
0answers
42 views

Reduce Random Forest Model Size

I've created a regression model on my data using random forests in R. The output is quite large, I'm wondering if there's any way to reduce this to only the necessary pieces to make a prediction? The ...
0
votes
0answers
32 views

How to explain the value of y-axis in Partial Dependency plot

sample numbers = n number of classes = 2 The function is $$F(x) = \sum_{i = 1}^nf(x,x_{ic}) $$ where $$f(x,x_{ic}) = \log p_1(x,x_{ic}) - \frac{(\log p_1( x,x_{ic} )+\log p_2( x,x_{ic}))}{2}$$ In ...
7
votes
5answers
227 views

How to perform imputation of values in very large number of data points?

I have a very large dataset and about 5% random values are missing. These variables are correlated with each other. The following example R dataset is just a toy example with dummy correlated data. ...
2
votes
2answers
105 views

random forest for large number of variables and predictions

I have very large number of variables compared to samples they are measured on. The following is example data in R. ...
1
vote
0answers
43 views

Random Forest and Factor Predictors [duplicate]

How do decision tree based ensembles like random forest deal with categorical ("factor") predictor variables? My guess would be that indicator variables are created for each factor via a ...
1
vote
2answers
55 views

what does the correlation of Random forest regression tool in R represent

I've built a random forest model (regression model) using randomForest package in R, and I calculate the correlation between the predicted values and the actual ones in order to know how the trained ...
2
votes
2answers
131 views

odds ratio from decision tree and random forest

I am using a decision tree and random forest for a classification problem. The output is binary {0,1} and some of the input variables are categorical while the others are continuous. I would like ...
2
votes
1answer
191 views

Relative importance of a set of predictors in a random forests classification in R

I'd like to determine the relative importance of sets of variables toward a randomForest classification model in R. The ...
0
votes
0answers
81 views

How do I get coefficients of a random forest model?

I am using randomForest to generate a model, and at the end I don't know how I can get the final coefficients that the model is fitting. I know that for linear ...
1
vote
0answers
483 views

R: What do I see in partial dependence plots of gbm and RandomForest?

Actually, I thought I had understood what one can show a with partial dependence plot, but using a very simple hypothetical example, I got rather puzzled. In the following chunk of code I generate ...
3
votes
1answer
79 views

Finding interactions using randomForest

I am trying to use randomForest in R to find interaction terms to add to a model. My plan was to fit trees with maxnodes=4 (two ...
2
votes
1answer
89 views

Imbalanced training dataset and Random Forest regression model

I have a large dataset (>300,000 observations) that represent the distance (RMSD) between proteins. I'm building a regression model (Random Forest) that is supposed to predict the distance between any ...
1
vote
1answer
222 views

Confusion matrix calculation in random forest classifier in R

After training using random forests on the iris dataset, I get an OOB error and a confusion matrix. ...
2
votes
1answer
104 views

unbalanced samples random Forests

I am trying to predict species presence or absence using randomForest in R (classification). In fact, I am trying to do it for several species, in separate models. For a couple of the species, the ...
0
votes
0answers
65 views

Random forest highly imbalanced dataset: how to test _ create ROC curve?

I have a dataset containing 10,000 examples with 8 features. I would like to create a random forest to classify this dataset in two classes, more specific: substrate / no substrate. In this dataset ...
1
vote
0answers
266 views

Predicting and calculating test mse using cforest R

I'm new to the cforest package and am trying to create a cforest model to predict a new test set and calculate the model test MSE. My data is split into d.train ...
1
vote
1answer
210 views

Interpret Variable Importance (varImp) for Factor Variables

When I run variable importance on a random forest (or any other model), the factor/categorical variable names have the factor name as the suffix. For example, ...
0
votes
0answers
87 views

Interpreting RandomForest variable importance in case of multiple polytomous dummy variables

I have some trouble interpreting R's RandomForest variable importance measures when using multiple polytomous dummy variables. Take the following example: I have paired country data, e.g. ...
3
votes
1answer
139 views

Trend Analysis of feature importance over time in R

I'm running an experiment on a Streaming Classification Model (an Online Random Forest) that I've created. If that is a completely foreign concept to you here is a presentation I did on it recently: ...
1
vote
0answers
58 views

Random forest for binomial data

I have data where the response is of the form (k,n) - k successes, n trials for a given subject. The covariates are just some subject-specific predictors. Is it possible to use randomForest for ...
2
votes
0answers
59 views

Dissimilarity with earlier features part of cost function

I am using a RandomForest on features (pixels) of images, and I am considering adding cost for "similarity to already other included features" to the cost function. Imagine you have a current RF ...
2
votes
0answers
39 views

Identifying what weights to give to each class in a Random Forest

I am using a randomForest package in R to discriminate between 4 categories. My data consists of 80+ observations and is heavily unbalanced with around 70% of all observations being in a single ...
1
vote
1answer
115 views

How to model features with NULL (not necessarily missing) values

I’d like some advice on my options for modeling features (to be used in R) in the following scenario: I want to make a binary prediction using the positions of the planets as the predictors (the X’s). ...
1
vote
1answer
74 views

Weird bootstrap bias for Predictor Importance (MeanDecreaseAccuracy) in Random Forests

Below, using R, I: 1. Create a data set with a bunch of factors. All of them are predictors and 'y' is the dependent variable. 2. I run a classification Random Forests for y with predictor importance. ...
3
votes
0answers
56 views

What is the purpose of working on a logit scale in partial dependence plots?

What is the purpose of working on a logit scale in partial dependence plots (in binary classification)? One could simply go about as follows: Grow a forest Suppose ...
1
vote
2answers
121 views

Weighting more recent data in Random Forest model

I'm training a classification model with Random Forest to discriminate between 6 categories. My transactional data has approximately 60k+ observations and 35 variables. Here's an example of how it ...
0
votes
0answers
54 views

multiple time series classification using randomForest R

I have daily time series of all constituent stocks/members of the S&P500, over a 5 yr horizon, and wish to classify as to whether a stock will report an "earnings revision" via a binary outcome ...
1
vote
1answer
831 views

Issue on prediction with FinalModel of RandomForest in R using the CARET package

I use the caret package for training a randomForest object with 10x10CV. ...
0
votes
1answer
100 views

Random Forest variable importance metric for predicted value

Let's say I'm using a random forest in a true/false classification problem. When I produce a score for an observation is it possible to get some sort of metric of variable importance for that ...
4
votes
1answer
321 views

Can Random Forests do much better than the 2.8% test error on MNIST?

I haven't found any literature on the application of Random Forests to MNIST, CIFAR, STL-10, etc. so I thought I'd try them with the permutation-invariant MNIST myself. In R, I tried: ...
3
votes
0answers
51 views

“optimum” tree from random forests [duplicate]

You can get sample trees from random forest (e.g., see: How to actually plot a sample tree from randomForest::getTree()?) However, rather than getting a single tree from random forest, is there any ...
1
vote
1answer
79 views

Plot cost function for Random Forest against sample size in R

I would like to aestimate the cost function of a random forest model fed by several subsets of my training/test data. The subsets are increasing in size. Comparing the cost against the training and ...
0
votes
0answers
58 views

Random Forests and Feature selection [duplicate]

First, I split my training set into 10 parts. 9 parts of it, I use as LS and the other one as TS. I now want to do feature selection, so I do feature selection on 9 parts. I use Random Forest to do ...
1
vote
1answer
468 views

Does party package in R provide out-of-bag estimates of error for Random Forest models?

I'm a new R user, and also new to Random Forest modeling. I cannot seem to figure out how to obtain the out-of-bag (OOB) error estimates for cforest models built with the Party Package in R. In the ...
1
vote
0answers
168 views

Significance of R Squared in Random Forest / GBM and GBM Tuning Parameters

I often get different level of responses when I discuss about R-Squared and its relevance to measuring the performance of a Random Forest or GBM model. In general, RMSE is a better and more ...
1
vote
0answers
163 views

How to generate Random C4.5 Trees in R [closed]

I want to generate a forest using C4.5 trees, (the randomForest Package generates them using CART) Any suggestions on packages and commands in R?
1
vote
0answers
91 views

Organizing data to feed random forests

I'm willing to apply machine learning with R (I will start with random forests then maybe have a look at NNs) on some data, but I don't know where to start, ...
0
votes
1answer
307 views

random forest classification in R - no separation in training set

Originally posted on Stack Overflow, but suggested to move here... I'm new to machine learning, but I've tried to perform a Random Forest classification (randomForest package in R) on some ...