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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Python “feature_importances” for most important factors

I'm a little unsure as whether this belongs in stackoverflow or cross validated. I have found a few posts on this topic , but I have not found the following question. Is it accurate to run the feature ...
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16 views

Analysis of Feature Importances when features are dependent on one another

I can use random forests to determine which features are important when doing a prediction problem; for example. < height, weight, IQ measure> -> Is considered obese? Applying random forests ...
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9 views

How proximity and multidimensional scaling relate? #random forest

I have downloaded randomForest package of Breiman and try to use function MDsplot to plot the proximity of the data like the example in the manual ...
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43 views

Package ‘randomForest’ R defining variable importance in advance

I am planning to build 5 successive random forests (RF) on a same data using r 'randomForest' package. I am leveraging work done as per the page. while building the first RF, each X variable should ...
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20 views

regarding using Lasso and Random forest based on the variable selection result coming from other processes

After the process of data exploration process and discussion with client, we set up a set of variables as follows: T1, T2, T3, T6, T8, T2*T3, T1*t6 During ...
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24 views

Using an RMSE with derived confidence interval, to generate a prediction interval for an estimate

Previous questions have asked about creating prediction intervals for estimates derived from random forests or boosted regression trees, in a similar way to is easily achieved with linear regression ...
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17 views

input variables with different order of magnitude [duplicate]

I need to build a prediction model based on a data set with 5 different independent variables. The data set looks like as follows. The variables in col4 and ...
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42 views
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29 views

Random Forest Regressor - Incorporating Sample Weights in scikit-learn

I am running randomforestregressor in python. The target variable I am modeling is the frequency of an event occurring per unit of time. Each record in my data includes whether or not the event ...
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1answer
37 views

Using random forest for survival analysis with time varying covariates

I've been trying to train a model that predicts an individual's survival time. My training set is an unbalanced panel; it has multiple observations per individual and thus time varying covariates. ...
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28 views

Is 100% accuracy using randomForest indicative of anything wrong?

I am getting a 100% accurate result on randomForest model in R for loan default data even when my training set and test set are completely non-overlapping. I am using abt 8 parameters/features for ...
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26 views

How does the R library “randomForest” order factor levels?

So my question is, which level gets number 1, which one gets 2.. etc. I speculated that it could be the order in which they appear in the input / alphabetically, but none of these seem to be correct. ...
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19 views

Random Forest partial plot

I have the following graph generated after I used the partial plot function of Random Forest in R. Now from this image, my understanding says that temperature has a linear relationship with my ...
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2answers
103 views

How can I get more precise regression tree?

I am a complete newbie to regression trees so maybe I am not understanding it properly. I got the following tree from my analysis (function tree() from R package ...
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1answer
55 views

Relationship between Gini Importance and Prediction Performance (say AUC)?

I want to use the decrease in Gini impurity to rank features for my random forest classifier. I understand that the decrease in Gini impurity at one node is calculated as: $$ \Delta i(n) = i(n) - ...
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2answers
74 views

Analysis for checking if an Ensemble model is a better fit for a dataset than Primitive model

I have a dataset and have the option to apply either GLM (primitive) or a Random Forest (ensemble). So far the Random Forest is giving way better results than the GLM. As it is generally believed that ...
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63 views

Caret feature selection with customized random forest classifier

I'm following the Caret package tutorial for constructing customized functions for a recursive feature elimination. I can reproduce the provided example which is a random forest regression. However, ...
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65 views

interpreting y axis of a partial dependence plots

I have read through other topics on partial dependence plots and most of them are on how you actually plot them with different packages, not how you can accurately interpret them, So: I have been ...
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1answer
26 views

How to define samples in caret package?

I am using the caret package and need to train a random forest, where only certain samples should be in the held-out set. I want to define the sampling for each tree in the random forest, for say 100 ...
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1answer
52 views

How to measure when error stabilizes (convergence) on Random Forests (or, when do I stop training)

I'm doing an implementation of Random Forests. As I was the original paper (page 11) and this nice book on the subject (15.3.1, page 592), they mention that when the out-of-bags error stabilizes (when ...
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22 views

Better calculation of ends of the curve when using R's RandomForest?

I've been using R's randomforest library to predict a series of (2000) products with prices ($10-$2000) and I'm noticing the low and high ends of the continuum are least accurate, especially when I ...
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2answers
67 views

Different results from several “passes” of Random Forest on same dataset

I've been playing around with the German Credit dataset available in Kuhn & Johnson's caret package for ...
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2answers
50 views

Will RandomForest model work well if the correlation lies between the given attributes

Currently I am working on the data mining project and I am using RandomForest classification model for that. I have a few queries in that. Will the RandomForest handle if there is correlation ...
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2answers
115 views

random forest variables importance with continuous and categorical variables and unbalanced output

I am a bit lost in the literature regarding the random forest importance. I am aware that there are different methods. I have a binary output variables where elements labelled with 0 are much ...
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26 views

Accuracy low if test data belong to a single class

For my classification task I have two classes labeled 0 and 1. I am using Random Forests from sklearn package in python. I have two files for different classes. So I loaded the files, combined them ...
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18 views

randomForest sample size value formula

This question has been asked previously, but the answer didn't contain a formula - only a rule of thumb heuristic. Is there a formula or rule that exists for determining the appropriate sample size ...
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1answer
92 views

Random Forest confusion matrix

I've been creating some random forest models using the caret package in R. I don't have a large amount of data to work with so I'm using 10 x 10-fold CV in lieu of an independent test set. When I ...
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1answer
41 views

Is the random forest solution for regression interpretable and sparse?

I have a regression problem scenario. Basically, I want to model a certain biological problem with regression models and at the end my model should be interpretable. I need to have a sparse model. So ...
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57 views

Difference between tuneRF {randomForest} OOB error and Model OOB error

I have used tuneRF {randomForest} function to know best mtry and got OOB error is almost 19%, however when i run the model using randomForest am gettin OOB error 28%. I am running the model on same ...
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1answer
76 views

How can you print the decision tree of a RandomForestClassifier

Recently, I have noticed that there is a method sklearn.tree.export_graphviz documented here. However, I do not know how I can apply it to a ...
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29 views

R - randomForest - rfcv function - explanation in laymans terms

My name is Abhi and I am trying to teach myself data science by solving problems on the internet. In my current model I am using a random forest & the rfcv function to test the performance of the ...
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40 views

Random Forest - Huge Disparity between OOB Error and test data error

I am building my model in R and am using the randomForest package. My current model has 7 features and I see OOB error rate of about 14%. I also ran the rfcv in the random forest package to see how ...
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27 views

Using min leaf size above 1 in random forest/treebagging

Are there any advantages in using a min-leaf-size above 1 in classification with bagged trees(/random forests)? I would imagine that it could make the classification more robust as some area in the ...
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18 views

improving randomForest running time

This has already been asked and answered, but one of the answers didn't explain why a certain technique worked. So my question is "Why does calling randomForest(predictors, decision) instead of the ...
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1answer
47 views

Feature selection when bagging trees/random forest

I want to get a better understanding of feature selection and how the number of features affect performance when bagging trees. I am using Matlab's treebagger and I ...
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1answer
75 views

Predicting customer churn - train & test sets

I'm struggling with a problem where I'm trying to predict customer churn. I have monthly snapshot data going back several years, and tags for whether a customer left during a given month. My main ...
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48 views

Pitfalls of using random forest/GBM on proportion data?

I have a set of data with a dependent variable which represents a proportion, and many of the samples contain a response of 1. I would like to build a random forest or GBM regression model on the ...
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1answer
51 views

Is there a way to explain and generalise the decision made by random forest?

I saw a similar question was asked a few years ago, maybe there are updates on that. I would like to have a way to explain the decisions generated by random forest, possibly in a single tree. I ...
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1answer
41 views

Factor Analysis vs. Random Forest Feature importance

Could someone explain the intuition behind the difference of feature importance using Factor Analysis vs. Random Forest Feature importance. Does there lie an advantage in RF due to the fact that it ...
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24 views

Polling vs averaging in Random Forest models

Why is it that for Random Forest we take the average vote from each classifier in the ensemble rather than the average probability from each classifier in the ensemble? Is there theory behind why ...
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17 views

When is data slicing (and training separate models) worthwhile?

This question is more general about when one decides to train models on separate slices of a data set, rather than just one model on the entire training set altogether. So I'm working on a ...
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1answer
41 views

mtry tuning given by caret higher than the number of predictors

According to this discussion, it seems that the train function of the caret package returns a ...
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14 views

Dealing with numbers-based categorial data in rf regression: to standardize, or encode?

I'm working with the SEER cancer dataset, and I'm trying to use regression to calculate the months a breast cancer patient can expect to survive given certain variables. Some of these variables are ...
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21 views

Creating obligatory combinations of variables for drawing by random forest

Problem For my machine learning task, I create a set of predictors. Predictors come in "bundles" - multi-dimensional measurements (3 or 4 - dimensional in my case). The hole "bundle" makes sense ...
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1answer
27 views

With Random Forests, is it possible to provide an error term for each variable or each sample?

I'm wondering if there are any implementations of random forests that allow one to provide error terms for the inputs. An error term could be based on a per-variable basis, or on a ...
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32 views

Constructing Random Forests for binary classification by minimizing entropy

I'm looking to perform a binary classification using random forests, but I do not quite understand how to minimize the entropy of the data / what tests I should run on the nodes to do so. I'm fairly ...
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48 views

Why does Random Forest Regression perform worse than autoregression

I have a dataset of NFL games. Each game has one row for each team in the game. Each team's row contains the team's statistics in that game (such as points scored, passing yards, red zone attempts, ...
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1answer
68 views

Random Forest proof notation

I am having a bit of difficulty understanding the notation in equation (1) on page 4 of the following paper: https://escholarship.org/uc/item/35x3v9t4#page-4 Specifically, what do $E_{X,Y}$ and ...
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46 views

Random forest - proof of convergence

I'm having some trouble understanding Leo Breiman's proof that the generalization error of a random forest converges as the number of trees increases (here's a link to the paper). At Appendix I he ...
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20 views

Conditional Forest - Calculate Overfitting, OOB Error

My name is Abhi and I am trying to teach myself conditional forests. I have got a basic example working myModel <- cforest(Survived ~ .,data = ...