Random forest is a machine-learning classifier based on choosing random subsets of variables for each tree and using the most frequent tree output as the overall classification.

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22 views

Propensity score matching: using alternative methods to create a distance measure

I would like to use a greedy nearest neighbour method to do propensity score matching. Though I've little experience here, it seems that the distance measure used is generally a propensity score ...
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24 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 ...
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1answer
24 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 ...
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2answers
37 views

Test data results does not match with cross validation results

I'm confused with my data I'm currently playing with. I have a data set which holds 58 attributes in 10000 instances. Attributes are 56 float values typically within 0 to 1. Then there is nominal ...
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1answer
49 views

Random Forest can't overfit?

I've read some literature that random forests can't overfit. While this sounds great, it seems too good to be true. Is it possible for rf's to overfit?
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10 views

Correct Evaluation of Random Forest on fixed training/test set

I have to test the performance of Random Forest on the same dataset (text classification) with about 118.000 instances of which about 1/3 is used for training and 2/3 is used for testing. The division ...
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0answers
17 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 ...
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63 views

Why does the scikit-learn bootstrap function resample the test set?

When using bootstrapping for model evaluation, I always thought the out-of-bag samples were directly used as a test set. However, this appears not to be the case for the scikit-learn bootstrap ...
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18 views

feature selection for longitudinal data

I have a longitudinal data which looks like this. Number of time points are different for each ID. Y is the binary response variable (take values 0 & 1) and X1-X20 are either continuous or ...
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36 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 ...
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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 ...
3
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2answers
66 views

Linear post-treatment of nonlinear regression

I have often found in practice, using nonlinear regression techniques such as feedforward neural nets or random forests, that the resulting actual-vs-fitted plot (on training set) seems obviously ...
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2answers
58 views

How does random Forest work for regression?

I am an absolute beginner in field of machine learning, I started doing titanic assignment in Kaggle and found(read some where) Random Forest is the best fit. I started reading about random forest and ...
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1answer
58 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 ...
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0answers
8 views

Does within-group heterogeneity negatively impact random forest classification?

I have two rather conceptual questions about random forest classifiers. Before we get there, I quickly want to lay out the problem I am working on: I have large a large data set consisting of 300 ...
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2answers
152 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
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1answer
15 views

Use random forest outliers to detect group of variables

I have a input data and an output binary variable . The y value is 1 if the patient get ill. ...
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1answer
43 views

Post hoc selection of important features in random forest?

I want to guarantee a parsimonious random forest (few features used). What are methods to do this? It was suggested to me to get the feature importance after the model was created, and then create a ...
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0answers
13 views

Considering non-i.i.d. covariates in random forests

Random forests are theoretically funded on the assumption that the data are i.i.d. realizations from a multivariate random vector $(X_1, \ldots, X_p, Y)$. Does it make sense to use random forests (for ...
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4answers
114 views

Random Forest - How to handle overfitting

I have a computer science background but am trying to teach myself data science by solving problems on the internet. I have been working on this problem for the last couple of weeks (approx 900 rows ...
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0answers
22 views

How to deal with a feature relating to what type of expert labelled the data that becomes unavailable at point of classification?

Essentially I have a data set, that has a feature vector, and label indicating whether it is spam or non-spam. To get the labels for this data, 2 distinct types of expert were used each using ...
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4answers
80 views

Interpreting conflicting results from Random Forest & Logistic Regression?

I am using SKLearn and Statsmodel in python to build a RF and Logistic Regression, respectively. I have a feature that the RF indicates is important (feature importance of 0.202, closely behind #1 ...
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0answers
14 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.
2
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1answer
43 views

finding global minima of a random forest estimator

I have a random forest regression model with 1000 trees, having 16 parameters (using python scikit-learn). The estimator can predict a target value with cross validated r2 score of 0.87 +/- 0.03. I ...
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1answer
44 views

How to avoid random forest overfitting and improve prediction?

I have an input dataset x_train and an output dataset y_train ...
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0answers
13 views

On population variable importance

Consider we run a random forest on $n$ independent realizations of a random vector $(X_1,X_2,X_3,Y)$ assuming $Y$ is a numerical response variable. Let $f$ be the best theoretical classifier defined ...
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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: ...
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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: ...
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25 views

Is it necessary to do $k$-fold cross validation for decision trees in random forests?

Consider the following data set train: ...
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9 views

How to replace missing values with unsupervised random forest?

from http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm#unsup : Formulating it as a two class problem has a number of payoffs. Missing values can be replaced effectively. Outliers ...
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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 ...
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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 ...
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1answer
40 views

Is it possible to assign class probability to a random forest prediction?

When making predictions with a random forest model, is it possible to associate the probability of a test case belonging to a class? For example, for a given test case, can we say that the probability ...
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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
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1answer
97 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 ...
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0answers
51 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). ...
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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 ...
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0answers
27 views

Justifying unsupervised clustering using Random Forest?

I have been looking at ways to carry out unsupervised clustering of data with both numeric and nominal (but not ordinal) variables. I also suspect non-linearity in the data. A possible solution would ...
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1answer
87 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 ...
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1answer
67 views

What is the equation for random forest?

I need an equation for random forest so that I can score fresh data I receive every week, based on beta estimates I got after building model using this ensemble methodology. Every week I do not want ...
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46 views

Random Forest: Important variables, Important values

I've been reading up on random forests and have come to a stumbling block in regard to their practical application (an probably fundamental understanding). This problem i in regard to important ...
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1answer
79 views

How do you validate your machine learning models?

I am wondering what approaches are commonly used for validating a classification or prediction models: Approaches that am using at the moment: Using truth-sets: - ROCs, Bootstrapping, Accuracy, ...
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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 ...
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0answers
19 views

Down-sampling with building models (specifically random forests)

I was wondering if anyone had ever used down-sampling to build random forests with data that has unbalanced classes. Basically down-sampling samples (with replacement) x*min from the population where ...
2
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1answer
38 views

Do random forest variable importance measures take into account the interactions?

Do random forest measures of variable importance (mean change of accuracy, mean change of Gini index) take the interactions into account? I think I know how we come up with the variable importance ...
0
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1answer
29 views

What's the best way to calculate survival time using outputs from random survival forest

I have built a random survival forest using R package randomForestSRC. The OOB error rate is around 10%. I was wondering whether anyone had some experience in utilizing the outputs from this model ...
0
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3answers
161 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
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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, ...
2
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2answers
71 views

How to get rid of bias in data?

I have been trying to classify a set of data into one of four classes. The data has already been generated and I have set aside 10,000 for training and 2,000 for testing. I have also generated the ...
5
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2answers
70 views

How would one formally prove that the OOB error in random forest is unbiased?

I have read this statement many times but have never come across a proof. I would like to try to produce one myself but I'm not even sure on what notation to use. Can anyone help me with this?