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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R -Pediction Interval of Random Forest [on hold]

I am using quantregForest package to calculate the prediction interval, but the results are disappointing. The code is: ...
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15 views

Random Forest online/incremental learning in R

Is there a Random Forest implementation available in R, that supports online learning? My alternative approach was to use the popular randomForest package and combine Random Forests (the existing one ...
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24 views

How to deal with garbage data with Random Forest?

I'm using scikit-learn's RandomForest to perform a multi-class classification task, with examples from N classes and "garbage" examples not from the N classes. Because the garbage examples might ...
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10 views

**Kappa measure in Random Forests** [on hold]

Following is the detailed summary of trained model by Random Forests: ...
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34 views

How to get the most important variables in random forests in R?

I am building a random forest in R and was wondering how to extract the most important variables. I am using a random forest to classify if a click is fraud or not, and the goal is to identify ...
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1answer
38 views

Which samples are used in random forests for calculating variable importance?

Each tree of a random forest is learned on a random bootstrapped sample. Consequently, given that the number of trees is large, it is probable that every observation of a data set is used to form at ...
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5 views

Evaluate and report fit of a model on validation cohort(s)

I trained a random forest regression model M on a training set. I am interested in how well the model predicts the responses in 3 different validation sets. I am also interested in the characteristics ...
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2answers
27 views

Specify fake-numerical categorical feature to Random Forest?

Suppose I have a mixture of some categorical features and numerically continuous features. I would like to train a classifier based on the features by RandomForestClassifier() in SciKi Learn. Random ...
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23 views

Manually adjusting (stretching) a random forest regressor model

So I have a random forest model (sklearn) fitted to about 3000 data points. It has a poor OOB score (0.3) but it's not completely surprising due to the data set being social media based. The ...
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12 views

How to sign and score (risk) factors in a Guided Regularized Random Forest?

I have a guided regularized random forest (RRF-GRRF) model which predicts if students in a class will drop out of school. I need to make a report that indicates for each student which factors ...
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2answers
289 views

My Test accuracy is pretty bad compared to cross-validation accuracy

I did a Multi-class document classification. I divided the original data set (18,8334 documents as a list of strings where each element of list is a document string.) into 70% training and 30% test. ...
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1answer
25 views

Class-specific feature importance

I have rather a simple question which I have not had any luck finding the answer to. I'm training a Random Forest classifier using sklearn in Python 2.7, on a large dataset ~(80k,250) where ...
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21 views

Random Forest Underfitting

I am running a random forest for different sets of data, with an attempt to make it dynamic enough to optimize for all sets of data (they are are similar data sets). There are around 150 predictor ...
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24 views

attrition model using random forest

I am using random forest in R to predict attrition. In the training data set 70% of the customer attrited. Following are the questions 1) can I down sample the data set with 50-50 of both the ...
3
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1answer
107 views

How to reduce number of false positives?

I'm trying to solve task called pedestrian detection and I train binary clasifer on two categories positives - people, negatives - background. I have dataset: number of positives= 3752 number of ...
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36 views

Variable importance using cforest in clustering / unsupervised learning application

I have a data set which I'd like to cluster by using random forest. As I have more than 50 variables, I first want to identify the most important features and subsequently cluster the data set based ...
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25 views

Improving randomForest model

I have following data and code to create a model with randomForest with 80% of rows as training set and 20% as test rows: ...
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3answers
41 views

How to use Random Forest for categorical variables with missing value

I have a labelled dataset of 1M rows and 600 features. I am trying to build a supervised learning model for prediction. I am particularly working with Random forests in R.The data I have has following ...
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2answers
78 views

How to reduce error rate of Random Forest in R?

I want to build a prediction model on a dataset with ~1.6M rows and with the following structure: And here is my code to make a random forest out of it: ...
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1answer
55 views

Logistic Regresion / SVM / Random Forest Implementation in Matlab

I would like to implement (L2-regularized) Logistic Regression, (L2 regularized) SVM and Random Forest for multiclass classification in Matlab (without using a toolbox or the corresponding functions ...
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1answer
63 views

Random forest and model predictions

I have a working random forest model (classification tree) in R that I made with a training dataset. I used the predict function with a verification dataset: ...
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1answer
55 views

Random forest vs Adaboost

In section 7 of the paper Random Forests (Breiman, 1999), the author states the following conjecture: "Adaboost is a Random Forest". Has anyone proved, or disproved this? What has been done to prove ...
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1answer
36 views

Random Forest - What training set measure is the best predictor of test set accuracy?

I'm running a random forest model on a training sample in R in order to make predictions on a hidden test set. I'm having difficulty in understanding how I should go about improving my model in order ...
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1answer
39 views

Random forest regression prediction for high dimensional data

I am working on a project by using a high dimensional data set. Close to 50000 Obs. with 392 Variable. I used lasso to reduce it to this point from a total of 1200 variables. And the whole data set ...
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22 views

Python: In which cases will random forest and SVM classifiers can produce high accuracy?

I am using Random Forest and SVM classifiers to do classification, and I have 18322 samples which are unbalanced in 9 classes (3667, 1060, 1267, 2103, 2174, 1495, 884, 1462, 4210). I use 10-fold CV ...
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56 views

ARIMA vs. Random Forest

We have some power load functions that of course are driven heavily by a workday rhythm that we need to forecast, and after some light research into the topic, I see that using ARIMA would seemingly ...
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1answer
44 views

out-of-bag error estimate for Boosted Trees

In Random Forest, each tree is grown in parallel on a unique boostrap sample of the data. Because each boostrap sample is expected to contain about 63% of unique observations, this lefts roughly 37% ...
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55 views

Meaning of y axis in Random Forest partial dependence plot

I am using the RandomForest R package and am confused at how to interpret the values of the Y-axis in their partial dependence plots. Help docs state that the plot ...
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2answers
52 views

Unstable variable importance ranking

I am new to R and and random regression forest. Right now I am working with a dataset of 60 input variables (dummy variables and continuous variables) and try to find the most important variables, ...
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34 views

Huge overfitting with Random Forests and Boosted Trees?

In the following picture, the boxplots represent a performance metric (the closer to 1, the better) recorded for 50 runs of cross-validation, and the black filled circles are the training values of ...
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1answer
48 views

LOOCV $R^2$ higher than regular $R^2$ in RF

I am working with RF and the caret package, and I am having a confusion because sometimes the LOOCV $R^2$ is higher than the regular $R^2$. Is it right? How can I interpret this? Here an example ...
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2answers
81 views

Are Random Forests and Boosting parametric or non-parametric?

From this excellent paper by Breiman, we can seize all the difference between traditional statistical models (e.g., linear regression) and machine learning algorithms (e.g., Bagging, Random Forests, ...
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1answer
70 views

What is the honesty condition for regression trees?

I have a question pertaining to Stefan Wager's "Asymptotic Theory for Random Forests": http://arxiv.org/pdf/1405.0352v1.pdf Wager first states that trees are "fully grown in the sense given training ...
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19 views

I observed very different feature scoring from two different classifiers. What does it really mean?

Here what I've done. Given the dataset, I run a Random Forests and Logistic Regression with 5 Fold Stratified Data Sampling. Then I plot the feature importance for Random Forests and Logistic ...
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1answer
40 views

Random Forests overfitting/unbalanced classes?

Suppose I am using random forests where the classes are highly unbalanced. How do you detect over fitting and what can you do to avoid it? Breiman says in his paper that random forests do not overfit, ...
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33 views

Resample random forest OOB to choose number of trees?

My post was inspired by this one (http://stackoverflow.com/questions/29290916/scikit-learn-random-forest-classifier-how-to-produce-a-plot-of-oob-error-agains) Although random forest models do not ...
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1answer
37 views

Different probability values when using DecisionTreeClassifier and RandomForestClassifier

I'm studying the Random Forests and I made a little example to validate my knowledge. I create two classifiers, one with the DecisionTreeClassifier and another with RandomForestClassifier. After I ...
3
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1answer
77 views

Effect of categorical interaction terms with random forest machine learning algorithm

Thanks in advance for the help. I have moderately large dataset (around 7000 samples) with numerous categorical predictors and a single binary response. All of the predictors are categorical. ...
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70 views

caret: using random forest and include cross-validation

I used the caret package to train a random forest, including repeated cross-validation. I’d like to know whether the OOB, as in the original RF by Breiman, is used or whether this is replaced by the ...
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1answer
49 views

Machine learning framework for SVM, Random Forest

I need an library, or something that is already done for SVM and Random Forest algorithms. Can you give me some ideas? I don't have experience and I don't know what to choose. The restriction of my ...
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8 views

Classifier with interchangeable features

I have a situation in which the features used in a classifier are multiple instances of the same kind of measurement, in random (or unknown) order; thus, a sample x1, x2, ... xn -> classA could with ...
3
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1answer
94 views

Plotting learning curves for any classification algorithm

As recommended by Andrew Ng in his great course on machine learning, I would like to plot the learning curves for experiments I am running with Random Forest and SVM algorithms. The learning curves ...
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20 views

feature slection in random forest in python

I have a dataset consisting of 24 numeric features and about 7000 rows, i am applying random forest to get the binary classification, So please tell me how to find only the relevant features to get ...
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27 views

Best Random Forest model converging to bagging: What does it mean? (R)

I am performing a grid search to tune the Random Forest parameters m and nodesize. I have 79 variables, and the best model, in terms of OOB error, is a model with 76 variables (OOB error = 0.137). So, ...
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0answers
82 views

Random Forest accuracy 0.98, is it too much?

I am using about 256 predictors and target is sales. I am using a software called Alteryx which is R based. I have tried to run Random Forest, Spline model and Neural nets on same data. I used ...
4
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50 views

Does Breiman's random forest use information gain or Gini index?

I would like to know if Breiman's random forest (random forest in R randomForest package) uses as a splitting criterion (criterion for attribute selection) information gain or Gini index? I tried to ...
2
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1answer
61 views

Negative $R^2$ at random regression forest [duplicate]

I am currently writing my master's thesis about random forests and just started to work with the R software. When I am running my model the output looks like this: ...
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2answers
68 views

R randomForest R replace=TRUE pro's and con's

When using R randomForest package I use replace=TRUE, which then dictates to: if (replace) nrow(x) else ceiling(.632*nrow(x)) I was wondering if anyone knows of ...
4
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1answer
203 views

Should you tune 'ntree' in the Random Forest algorithm?

In the original paper, I was under the impression that the RF couldn't really overfit. However, in practice I'm seeing that increasing 'ntree' sometimes increases test set error. Is this due to ...
0
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1answer
41 views

Applying randomforest algorithm (fit) on new data without recomputing the fit [closed]

I have a need to do realtime predictions for individual rows of data based on a previously computed randomForest algorithm. How can I run the "predict" command without recomputing "fit" on the entire ...