Random forest is a machine-learning method based on combining the outputs of many decision trees.

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Random Forest Logloss question [on hold]

I am learning how to use random forest. When I use logloss function to compare my predict model with test data, I got a number greater than 1. Here is my model: ...
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Predicting the status of an individual across time [on hold]

In my case my training data frame is like the following : Id|Month|Status|Others 1|01/16|O|X 2|01/16|O|X 3|01/16|O|X 1|02/16|E|X 2|02/16|O|X 3|02/16|F|X 1|03/16|E|X 2|03/16|O|X 3|03/16|F|X ...
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1answer
44 views

Are numerical variables must for random forest algorithm?

I am trying to find the variable importance on a credit scoring database. I have categorical inputs as well as numerical inputs. My question is does the random forest algorithm works the same way when ...
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1answer
37 views

Scalable Random Forest For Massive Data

My problem is simple. I want to train a dataset using random forest on a huge dataset (with $n$ rows). Let's assume I can only fit $b < n$ rows in memory at a time. Model Choice I see several ...
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16 views

plot accuracy of classification in Random forest and SVM in R

I have a question and I will be grateful if you help me. Is it possible to plot admixture or pure of individuals with Random forest-SVM methods (models) in R . Is there command for this work?
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36 views

References for learning about online random forests

I am new to concepts of random forest. Can someone provide relevant sites where I could get learn more about using random forests to learn incoming data like an online algorithm?
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lasso regression on top of random forest

Some time ago, I found a paper describing usage of lasso/elastic net regression on binary variables come from random forest. In short, (i,j)-th variable takes 1 if given observation belong to leaf no. ...
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1answer
35 views

Random Forest in R - most important variable causing errors

I'm trying to fit a Random Forest model in R. I've got a DF with 13 factorized variables plus the target one (binary). When I try to use all the variables with ...
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1answer
57 views

ROC Curve for different classifiers

I am trying to compare the classification performance of different classifiers. So far, I am using SVM, Random forest, Adaboost.M1, and Naive Bayes. 70% of data is used as training (and then plotting ...
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36 views

Machine learning approach when facing low predictive power features

My dataset has 3.6k samples and 600+ one-hot encoded features. Each feature has between 5-2000 instances, averaging around 150. Intuitively, I don't believe that my features should have much ...
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12 views

MSE and %var(y) in randomForest

I'm making my first trials with randomForest and I have a question about the output of the do.trace = TRUE parameter. It gives ...
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1answer
43 views

the trees in a Random Forest

What I want to ask is as follows: Is it possible that there are many identical trees in a Random Forest? If there was very little different training data in a tree sample by bootstrap aggregating, ...
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Is the offset_column parameter in H20's random forest algorithm the same as the offset option in SAS Proc Logistic?

I am trying to use H2O in R to run a random forest. http://docs.h2o.ai/h2oclassic/Ruser/rtutorial.html In the documentation, I saw that there is an option for an offset parameter but I cannot find ...
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18 views

Ranking of the prediction

I am currently using random forest to predict fraud on contracts. Each day, we predict the contract of the past day. The problem is, the guys I am working with keep telling that the value we should ...
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1answer
36 views

Training and test sets in random forest regression

Why do I keep reading about specifying training and test sets with random forest regression? As probably obvious from this question I am new to this method, but what I thought one of the cool things ...
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7 views

Dataset dimension with ExtraTrees

We are using an ExtraTrees with Fitted Q-Iteration, and testing it with different size of dataset, all generated in the same way. FQI seems to have very good performance with small dataset, but it get ...
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1answer
22 views

Convert categorical data with large number of levels to numeric data and what kind of mapping to use

I have a dataset with 20,000 rows and 11 columns. Out of the 11 columns 10 are categorical. Out of the 10, three have very large number of levels. i.e. levels >60. One of the variable is basically ...
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1answer
18 views

How do GBR trees differ from random forests regression in terms of predictive performance?

Is there a case when one would use gradient boosted regression trees instead of random forests regression (or vice versa)? It appears gradient boosted regression trees have done far better in ...
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Is feature engineering relevant at all for Random Forests?

Random forests is an ensemble of trees that learns the hidden patterns in the data. I have mostly tried doing some feature-engineering before running the Random Forest model but is it required or the ...
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7 views

RandomForest undersampling non events

I have data that is about 50 to 1 nonevent to event (in this case, purchases). I was taking an equal, or close to equal, sample of nonevents to events with a random forest model, and running the ...
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19 views

Need new strategy for single class classifier

I am attempting to create a single class classifier where the classes are fairly close to balanced (+/- 25). My dataset has ~2,800 samples and ~1,100 features. All of the features are binary except ...
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1answer
35 views

In a random forest algorithm, how can one intrepret the importance of each feature?

I am in the process of building a Random Forest algorithm in MATLAB using the TreeBagger function. In the documentation, it returns 3 parameters about the importance of the input features. My ...
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23 views

Random Forest: Strange Feature Importance Results for Constant Variables

I've been using the RandomForestClassifier in python's Sklearn package to assess the importance of the features in a large dataset with features that are both binary and continuous. I've done quite a ...
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40 views

Multiclass classification question

I am working on applying Random Forests to a multiclass classification problem, where I have a set of 11 predictor variables and a response that can take the values of "Yes", "No", and "Maybe". In my ...
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1answer
39 views

Time Series forecasting with useful predictor variables

I am playing with time series data related to a issue ticketing system. The system logs all open tickets at any one point and my task is to predict what the volume of open tickets will be in 5,10,15 ...
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R: Plot trees from h2o.randomForest() and h2o.gbm() [migrated]

Looking for an efficient way to plot trees in rstudio, H2O's Flow or in local html page from h2o's RF and GBM models similar to the one in the image in link below. Specifically, how do you plot trees ...
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Out of Bag Prediction Error Estimate from Random Forest Regression (i.e., not classification) [closed]

I would like to use the OOB cases from a random forest fit to estimate the mean squared prediction error so I don't have to cross-validate. I am using the randomForest package in R. It is clear from ...
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How can one quantify the variable importance dilution effect in random forests (and similar statistical learning methods)?

In Applied Predictive Modelling (Kuhn, Johnson, 2013, p 202), the authors refer to a dilution effect whereby compared to a single tree or a classical regression technique, the difference in importance ...
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15 views

Create a predictive user model

I am a bit lost with creating a user model in R. I would like to create a model that predicts whether a user is likely to do an action or not, based on data on his past behaviour (Target variable ...
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1answer
53 views

In random forest, what happens if I add features that are correlated?

(Sorry for the potentially unclear English, not a native speaker) I'm training a random forest, trying to predict market shares of future stores on geographical areas. I have many features for these ...
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48 views

Random Forest model good train and test performance but bad “real world” performance

I am working on a classification problem where I need to classify objects based on a visual data. There are a couple hundred different classifications to be made and I have around a million plus ...
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37 views

How to know the importance of all the variables and levels in them using Random Uniform Forest in R?

I have a dataset containing 3 parameters (Region( factors - say US,UK,Aus,NZ),Domain or Industry( factors - say IT,Electrical,Mechanical) and Scope - good or bad). Using Random Uniform Forest package ...
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28 views

The meaning of Classification Accuracy

I'm working on San Francisco Crime dataset, and only get about 20% classification accuracy. I used Random Forest Method. So how I can Interpret the result? I did EDA firstly, but how can I use EDA to ...
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Random forest for forecasting univariate time series

I read few articles on random forest and its implementation in various fields. But I hardly found any literature on its implementation on forecasting univariate time series. Can it be used for ...
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Difference between rulefit and random forest

I'm trying to understand the difference between these a bit better. I understand pretty well how random forests work but I guess I'm more hazy on rulefit and how exactly it's different. I know rulefit ...
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Weights in adaboost/decision tree(cart)

I'm trying to implement adaboost using decision trees. But I'm confused over the weights. I am unable to understand how to incorporate weights in training process, how the formulas for node entropy ...
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Gini impurity and generalization error

Has anyone seen papers on relationship between information-based criterions (such as Gini impurity, information gain etc.) and generalization error? Is there theoretical justification of using such ...
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In Random Forest, why IncNodePurity is biased?

I've seen this statement many times, however, I could not find an explicit demonstration of why IncNodePurity biased (actually, how does one define theoretical value of importance, is not so clear, ...
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24 views

Do Random Forests use boosting

Ok so I think I have listened to a few wrong discussions on random forests because now I have a very confused question. With respect to Random Forests and bagging/bootstrapping, I'm good there. The ...
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36 views

Tuning Parameters for Boosting/Bagging/Random Forest

I want to use tree-based classifiers for my classifiaction problem. I'm thinking about bagging, boosting (AdaBoost, LogitBoost, RUSBoost) and Random Forest but I'm unsure about the tuning parameters, ...
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Out of Bag Error makes CV unnecessary in Random Forests?

I am fairly new to random forests. In the past, I have always compared the accuracy of fit vs test against fit vs train to detect any overfitting. But I just read here that: "In random forests, ...
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27 views

How to select a model from leave one out cross-validation

I have a set of 400 positive vectors and hundreds of millions of negative ones. I have split the data into a training and test set each of 200 positive vectors and lots of negative ones. I would ...
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40 views

Can trees or random forests learn ratios

This is a question about feature engineering for decision trees/random forests. Given two continuous variables X1 and X2, is it ...
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49 views

How to handle over-prediction in Random-Forest

I have a regression Random Forest model (generated using H2O and R). After tuning and building the model, I plot the predicted value vs. the labeled value of both the train and test datasets. In a ...
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23 views

Preprocessing Random Forest With Lots of Features

I'm working on a project for uni where I have to predict a two-class problem, related to acceptance (or not) of a patent demand. Initially, I have a dataset separated into training and test data. My ...
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15 views

Weka Experimenter Tool (xx/yy/zz) explanation

I am using Weka experimenter tool and I need help to fully understand how this count works. I found this explanation in a paper: The annotation v or * indicates that a specific result is ...
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16 views

Feature importance RF

What is the difference between 'DeltaCriterionDecisionSplit' in the Treebagger function and predictorImportance() function from tree ensemble in matlab? Thanks.
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8 views

R randomForest importance=FALSE behavior

From the R help for the values of a randomForest object: "importance - ...(if importance argument=TRUE) The last column is the mean decrease in Gini index ... . If importance=FALSE, the last measure ...
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Is there a method to plot the output of a random forest in R?

Nice and simple. I've spent two hours googling, reading cross validated, and several r blogs to attempt to find a simple method of outputting the representative tree in R. I was attempting to ...
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Drop in results upon addition of new features in random forest model

I am training a classification random forest for object detection in images. I have several features (like HoG, edge features etc) which work good enough separately. But when I train using all ...