1
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0answers
39 views

Random Forest for data imputation

Currently I am using Random Forest approach for Missing Values Imputation from missForest package in R. I faced the following problem: the algorithm works much longer than any other imputation ...
2
votes
1answer
25 views

R - ROCR Library - Understanding predict and prediction method

My name is Abhi and I am trying to understand the difference between predict and prediction. I am using the r language and my ide is rstudio. I have created a random forest model (r package ...
0
votes
0answers
19 views

How does one estimate the number of trees and the depth when using random forests?

I am using random forests for a class. I am predicting weight training. In scikit learn I always used a rule of thumb of a depth of 5, the depth x features rounded. I had 53 features, rounded to 50 ...
0
votes
0answers
38 views

Random Forest - understanding k fold cross validation

I am trying to improve my data science knowledge by solving problems available on the internet. I am currently using the R package randomForest to classify the ...
0
votes
0answers
30 views

R - Random Forest - Need help understanding the rfcv function

My name is Abhi. I am trying to teach myself data science by solving some of the problems available on the internet. My current data set has about 900 reccords & 10 features. I am trying to use ...
1
vote
1answer
62 views

How to change threshold for classification in R randomForests?

All the Species Distribution Modelling literature suggests that when predicting the presence/absence of a species using a model that outputs probabilities (e.g., RandomForests), choice of the ...
0
votes
0answers
15 views

Down-sampling the majority class-How can I assure that all rows are been picked?

My doubt is about Down-sampling. I have an imbalanced data and I have use down-sampling, but I am not sure if all rows has been picked at any fold I have been use 10 folds.
0
votes
0answers
5 views

Error when trying to export randomForest model to PMML [migrated]

I'm receiving an error when trying to export one of my 'regression' randomForest models to PMML. The code I'm using to generate the model looks something like this: ...
1
vote
1answer
86 views

calculating probability or filtering that certain subject is not in the particular cluster

I have a situation where there are n individuals and p features (variables). I do have their cluster information. Here is an example: ...
0
votes
0answers
26 views

Controlling overfitting with random forests for very high dimensional data

I'm using the randomForest package in R to analyse a genetic dataset of ca 100 samples with 10.000 genes. The samples are grouped into 5 classes, the smallest being only of 5 samples. I'm ultimately ...
0
votes
0answers
16 views

Predicting whether a potential sale will be won or lost

I am currently working on a project using a sales system and trying to come up with a way to use the current pipeline of potential sales to predict the amount of product that will be sold in the ...
0
votes
0answers
20 views

Conditional Inference Trees in R

Consider the following data set test with binary outcome variable z and predictor variables a,b,c. ...
0
votes
1answer
108 views

Caret varImp for randomForest model

I'm having trouble understanding how the varImp function works for a randomForest model with the caret package. In the example ...
1
vote
0answers
52 views

Low explained variance in Random Forest (R randomForest)

I am using randomForest in R for regression, I have many categorical predictors (all of them have the same 3 categories (0,1,2)) and I want to see which of them can predict the response (continuous). ...
0
votes
0answers
8 views

Boruta score goes to minus infinity

I'm running the Boruta algorithm with a $179\times 36$ predictor matrix and a numerical response. Most of the variables have a score going to -Inf. Should I ...
0
votes
1answer
91 views

Confusion between caret randomForest predict() results and reported model performance

This question seems related, but the consensus was that the issue had to do scaling the data, which I do prior to training, so I don't think that's the issue: Issue on prediction with FinalModel of ...
1
vote
0answers
57 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
165 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
36 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
119 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
45 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
37 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 ...
5
votes
2answers
182 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
47 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
70 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
88 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
32 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
11 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
62 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
37 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
258 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
120 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
46 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
1answer
43 views

Does Boruta feature selection (in R) take into account the correlation between variables?

I am a bit of a novice in R and feature selection, and have tried the Boruta package to select (diminish) my number of variables (n= 40). I thought that this method also took into account the possible ...
1
vote
2answers
72 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
159 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
261 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
112 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
1answer
733 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
99 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
104 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 ...
2
votes
1answer
366 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
134 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
74 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
387 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
311 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
102 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
148 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
65 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 ...