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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RandomForestClassifier Regression Probabilities [migrated]

Using sklearn's RandomForestClassifier, if the class is a float then it will predict with regression trees and the prediction will be a float. I am trying to use ...
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RandomGLM: data (responses) is not read as numeric [on hold]

I'm relatively new to R and I have a problem with randomGLM for prediction of a continuous variable. I read in four datasets which are comprised of a training ...
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How to interpret random forest importance numbers

I ran randomForest in R package using 7 predictors variables (x1 to x7). I repeated the test with 4 dependent variables (y1 to y4). The importance numbers (IncNodePurity) are plotted in following ...
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60 views

Multiple regression or anova or bestglm or forestplot or Boruta

I have data on a continuous health variable and following others: age, gender, height, weight, waist, city and season. I applied multiple regression and got following output: (age, gender, height, ...
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variable reduction before doing random forest in R

I have a dataset featuring around 50 predictors, some of which are correlated. Now I am trying to fit a random forest model in R for prediction purpose with this dataset. Because there are too many ...
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25 views

Random Forest Probabilistic Prediction vs majority vote

Scikit learn seems to use probabilistic prediction instead of majority vote for the model aggregation technique without an explanation as to why (1.9.2.1. Random Forests). Is there a clear ...
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Explanation for large difference in SVM and Naive bayes results

I have a dataset with 389 data evenly distributed into 6 classes. Each data has 1024 features. So my dimension is much larger than my observation data. I have tried to see some common classifiers on ...
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19 views

Which performance measure to report?

I've trained a random forest regression model using boot632 resampling and the caret package. The output of the model tuning process gives a few different performance measures. ...
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SVM heavily over fits the data (classifying Highly Unbalanced data )

I have a huge training set from which I am supposed to regress and classify, i.e I classify whether an event will occur or not and another task is to regress the intensity of the event in future. The ...
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Binary classifier issues

I am trying to predict if sales are going up or done given a specific set of features. The only thing I care about is precision here. In this context I tried a few classifiers ( SVM, Random Forest ) ...
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36 views

Visualize difference between 2 classifiers

I trained 2 binary classifiers with the same data (a Decision Tree and a Random Forest). They both made a prediction on the same test data. Now, I want to visualize the difference in classification ...
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What's the potential reason that by combining two feature sets the performance of random forest dropped?

I am building random forests on high dimensional, sparse, and class unbalanced training datasets (around 500 - 5000 examples) using two different feature sets. I did stratified 10-fold cross ...
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34 views

If random forests gives me a bad cross-validation score, should I trust it for feature selection?

I get an R^2 value of about 0.22 when I 10-fold cross-validate with my entire dataset. My main use for random forests is to analyze feature interactions. But should I trust the feature importances ...
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Random Forest Algorithm Where to start?

I need to solve a real time classification problem using random forest algorithm.Can anyone suggest any book,website where I should start looking it ?
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fragmentation problem in decision tree

I am taking a NLP class, in which it says decision tree has the fragmentation problem. It says ...
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1answer
15 views

For the given type of dataset, what would generally be the set of classifiers that should be tried to get the highest TPR for FPR = 0.01

I'm primarily looking to attain the maximum True Positive Rate for a small False positive Rate of say 0.01. The following is an instance: 1 37.33 228.39 0 77.060599 0.073384 0.052536 ...
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21 views

How is the best split point determined/predictor calculated in a regression random forest?

In a regression tree (I am particularly interested in random forest regression, but it seems like this can be generalised to regression trees as a whole) a number of random variables is selected at a ...
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1answer
56 views

Classification score for Random Forest

I'm learning about the Decision Tree and Random Forests. But there is something I don't really understand. I have a training set and a cross-validation set. I need to train different Random Forests, ...
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19 views

Important Variable Direction in Random Forests

In a logistic regression a positive/negative beta tells you that the direction that variable works. Is there anything in the Random Forest variable importance measures that indicates the direction of ...
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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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23 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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17 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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51 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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30 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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41 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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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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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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46 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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30 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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28 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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1answer
29 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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107 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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82 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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78 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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77 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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112 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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27 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
54 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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23 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
74 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
55 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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133 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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27 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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21 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
131 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
53 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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83 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
99 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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38 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 ...