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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Scikit Random forest pred_proba gives rounded off values

I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But strangely it outputs probabilities rounded to first decimal place ...
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Reduce the FP rate for a Random Forest (sklearn)

I am working with the scikit-learn random forest classifier and I want to reduce the FP rate by increasing the number of trees needed for a successful vote from greater than 50% to say 75%, after ...
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42 views

Model to predict Residuals of another model

I am using a random forest for a 2 class classification problem. But eventually using probability of class "1" returned by the model for my task and not the label. I get AUC of about 70% Then I ...
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25 views

Regression by random forest in R [on hold]

I've worked with artificial neural network in matlab to predict data. There were feed rate, cutting speed and hardness as input and surface roughness as output. But now I want to predict surface ...
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1answer
48 views

What functions do decision trees and random forests learn?

We know that training a function $y = f_\theta(x)$ (parameterised by $\theta$ in some fashion, for e.g., the class of linear functions) using data $\{(x_i, y_i)\}$ drawn i.i.d from some unknown ...
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4answers
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Why is Logistic Regression called a Machine Learning algorithm?

If I understood correctly, in a Machine Learning algorithm, the model has to learn from its experience, i.e when the model gives the wrong prediction for the new cases, it must adapt to the new ...
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1answer
37 views

What does “node size” refer to in the Random Forest?

I do not understand exactly what is meant by node size. I know what a decision node is, but not what node size is.
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1answer
33 views

Can I Interpret the impact of variables like positive or negative on the model by Random Forest, as I can do by Logistic Regression

I have created a model for prediction of candidates presence or not . I have used Logistic Regression and Random Forest . By Logistic Regression, I got coefficients associated with 100 features and I ...
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15 views

random forest analysis with random(clustering) varible

My data consists of presence/absence (PA) of a trait in 354 plants collected from 127 collection sites as response, and a set of 25 climatic continuous variables in each site as predictors. The ...
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1answer
60 views

R package for Weighted Random Forest? classwt option?

I'm trying to use Random Forest to predict the outcome of an extremely imbalanced data set (the 1's rate is about only 1% or even less). Because the traditinal randomForest minimize the overall error ...
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1answer
45 views

Including Interaction Terms in Random Forest

Suppose we have a response Y and predictors X1,....,Xn. If we were to try to fit Y via a linear model of X1,....,Xn, and it just so happened that the true relationship between Y and X1,...,Xn wasn't ...
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1answer
27 views

Random Forest: Predictors have more than 53 categories? [duplicate]

What is the solution when we want to apply the Random Forest function in R to a predictor with more than 53 categories? ...
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1answer
21 views

Why the result of Random Forest Algorithm change a lot when all the parameters are kept the same?

I want to do some classification of some dataset with random forest. When I run the same script twice, two totally different(almost 5%) result were given by the program. I want to know whether random ...
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11 views

How does weka combine the decision trees in a random forest?

When building the random forest, I am wondering if Weka combine the decision trees by averaging their probabilistic prediction or if Weka let each decision tree vote for a unique class? Thank you in ...
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44 views

Random forest for panel data

I have a dataset with observations from about 50 countries and 20 years. My dependent variable is binary and I was wondering if I could use random forest to do out-of-sample predictions. My problem ...
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28 views

How do I set probability thresholds for a logistic regression and cutoffs in randomForest model to get a good confusion matrix?

Whenever I run a logistic regression, I need to set the threshold so that it groups probabilities higher than the threshold to my positive group: ...
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30 views

Resources for machine learning for time-dependent data

For the past year, I have spent the majority of my free time learning a variety of ML techniques (boosting, random forests, neural nets, SVMs etc.), but I have not been able to find a lot of material ...
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1answer
43 views

Random Forest: Different performance between training set and test set?

I'm a newbie learning Random Forest. When I use this method to predict my outcome and check with the same data set (training set), I see that the model fits almost perfectly the data. But when I ...
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29 views

Balancing random forest via cross validation. Difference between sample weight and cutoffs?

My random forest model of a simple binary target (0, 1) and is producing unbalanced results. i.e many more false positives than there are false negatives. In addition, '1' is a low percentage class, ...
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1answer
28 views

Random Forest in Pose Estimation

I am having problem in understanding the number of feature input to the Random forest mentioned in the paper below. Shotton, Jamie, et al. "Efficient human pose estimation from single depth images." ...
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18 views

Loss function for Random forest

I am working on a random forest model in R and want to use a different loss function from the default. Does random forest implementation in R allow for arbitrary loss functions?
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1answer
43 views

Area under ROC curve for random forest

Does the area under ROC curve depends on which class is defined as default positive class by the random forest model? I am using ...
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32 views

RandomForest classification model with 100% accuracy is it real or something wrong?

Hi I am new to machine learning. I just created my first working RandomForest classification ml model. It works amazingly well no error and accuracy is 100%. I have used Apache Spark MLlib to ...
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11 views

Is there a minimum sample size when using cforest to run a random forest?

I have a data set made up of: 41 continuous variables a factor with two levels 25 replicates (rows) I want to carry out a random forest analysis to identify the variables that are important in the ...
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16 views

Is it possible to achive low error on MNIST using Random Ferns?

I'm new in machine learning and i want to study how to use random ferns. I read this paper Fast Keypoint Recognition in Ten Lines of Code and implement simple version of algorithm. But then I tried ...
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1answer
64 views

Why discrepancy between lasso and randomForest?

Following are 2 plots, one of lasso using glmnet package and other 2 from randomForest (variable importance) of the mtcars data set assessing variable mpg vs others. In the lasso plot, the blue and ...
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23 views

Relationship between OOB Error in Random Survival Forests and c-index

The error rate reported by Random Survival Forests is ( 1 - C-index ) using the OOB survival predictions, and I am trying to understand exactly what is the relationship between the C-index and the OOB ...
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32 views

Out-of-bag error and error on test dataset for random forest

Recently I'm working with random forest algorithms, due to their easy to use. I always devide my set into train and test subsets, usually out of bag error for forest build on train dataset is higher ...
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2answers
65 views

When does it makes sense to use Cross Validation?

My understanding is that cross validation is about using different chunks of the training data to train the model and average out the error estimation so that the variance is less. For example, in ...
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36 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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36 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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53 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
52 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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8 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
34 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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29 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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19 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
344 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
29 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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27 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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34 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 ...
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1answer
136 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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45 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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27 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
62 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
93 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
76 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
88 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
80 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
71 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 ...