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Questions tagged [random-forest]

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

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Random effect vs. fixed effect with a huge amount of dummies

I am interested in examining inventor features on their inventive performance using patent data. I have an unbalanced panel data of 7000 inventor-year observations on 3000 inventors over 15 years ...
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Asking opinion about random forests, chi squared and data permutation

I have a set of data of counts of hares in summer and in winter, which is very unbalanced: winter was too cold, and samplings were taken only in some 20 occasions, while during the pleasant summer the ...
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1answer
45 views

Are the same number of trees required to compare Random Forest against GBM?

My training set has 13,737 observations with 53 predictors. I need to compare the accuracy of Random Forest vs. GBM. For Random Forest, I set ntree = 128 [based on ...
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20 views

Are the same number of trees required while comparing Random Forest to GBM? [duplicate]

My training set has 13,737 observations with 53 predictors. I need to compare the accuracy of Random Forest and GBM. For Random Forest, I set ntree = 128 [based ...
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14 views

add constraints to random forest

I've got a 200 points dataset with the following features two Atomic elements: Pt, Cu, Pt..../ B/C/D/E and I want to use them to predict X. I want to study the importance of the atomic elements the ...
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11 views

Adding Bad Events from the past to the risk default model to avoid Down/Up sampling techniques

We have been trying to build a classification model for credit default prediction using two different models one being Random forest and another being the Logistic regression based scorecard model. ...
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1answer
28 views

New factor levels in testing data set not present in training data in h20.randomforest

In randomforest classification using h20 package, there are factor levels which are present in testing data but not in training data.There is a warning message in predicting the values of testing data,...
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26 views

How to put list of unordered elements as features into a random forest model

Assume that I have 3000 unique rows of data to train with. For each data point, I have a special attribute called $SomeFeatureList. This is a list of independent features (categorical features) that ...
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40 views

“Hierarchical” Random forests?

Background I am using Random Forest to classify ~900 objects based on a large number (> 80) predictors. I split these 70:30 for training and testing. The overall model does fairly well, giving an ...
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28 views

RandomForest - model not superior to NIR [on hold]

I am trying to use RandomForest with caret package in R to build a predictive model with a data frame of 2337 patients assessed on 49 variables. The dependent variable to be predicted is disease ...
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1answer
17 views

Is Gini index actively involved in splitting a Random Forest node?

Since there are many references that a RF uses a slightly different approach on splitting a node in comparison to Vanilla Bagging. Does Gini index play an active role in the split or it's just another ...
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1answer
32 views

Is bagging involved in the split of node of a tree of a Random Forest?

I know that using Bagging method in a RF, implies that the subset we give to the root node of each tree, has randomly selected Features and Attributes. I also know that during the split of a node ...
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17 views

temporal autocorrelation machine learning algorithms

I am trying find out the relationships of stream integrity against Land uses. I have 4-years of stream integrity data (1998-1999, 2004, 2009, 2014) and corresponding land use data of 1995, 2002, 2007, ...
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27 views

Random Forest Regression with sparse data in Python

I am working on a Random Forest regression model to predict housing prices. I have about 500k rows of data with the following information: 1.House area in square meters. 2.Number of rooms. 3.City. ...
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30 views

Statistical conclusions based on conditional trees

I have a complex dataset, number of features is much bigger than number of samples. The question is - which features are important for classification into 2 groups. I think that (after some ...
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1answer
29 views

I trained Python RandomForest and predicts well against test set. But how to predict against a new data set? [closed]

I have taken some online Python and ML courses but I haven't been able to find an answer to this question I have. Now the RandomForest model is trained and it predicts well against the the data it ...
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23 views

Classification model for recommender system?

I have some data for various customers choosing one of 'n' products or no product. I have some useful features for each customer. I can build a multi-class classification problem out of this data and ...
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14 views

Estimating the values of unknown subpopulation areas with only the known total population values in R

I probably should have posted it here first, but I have the full details listed on stackoverflow. https://stackoverflow.com/questions/54414182/is-randomforest-appropriate-to-figure-out-if-i-drop-a-...
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24 views

Disproportionate classification accurary between testset and entire dataset (Random Forest)

So I have a multiclass problem (16 classes, 58k samples), for which I decided to use the RandomForestClassifier. After some feature engineering and cross-validation I got a test set (13k samples) ...
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30 views

How p-value is calculated in random forest when using measure_importance?

I am using random forest for importance analysis of my variables. I use measure_importance() and at the last column, p values are given. I used R. I used randomForest() and RandomForestExplainer() ...
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1answer
38 views

Using separate models to predict unbalanced classes

I'm facing a scenario with 5 classes where a tabulation of the target variable yields: > 1 2 3 4 5 > 1010 1310 1080 2700 2620 As you can ...
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0answers
24 views

Random Forest Dissimilarity in plain ML English

I am currently studying the Random Forest algorithm for cases that involve unsupervised learning and I am struggling to understand what the Random Forest Dissimilarity concept is. So far what I ...
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1answer
62 views

Adjust thresholds in multi-class classification [duplicate]

I have trained a random forest classifier on a (highly-imbalanced) 3-class problem (A 1% of the data, B 96%, C 3%) and obtained probabilities for each of the three classes. Currently I assign an ...
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21 views

Interpreting units for random forest variable importance

I've trained a random forest for classification in R's caret package using the ranger method and impurity for measuring variable ...
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1answer
37 views

Out-of bag error in Random Forest

I am trying to code my own, simple version od RandomForest function in R for learning purposes. However I have a hard time understanding the concept of the out-of-bag error. Is it simply done by ...
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1answer
35 views

Performing random forest on spatio-temporal rasters

We are trying to train a random forest model on land-use and meteorological variables to predict daily concentrations of air pollution at a 1km resolution. Our input data consists of 1km raster stacks ...
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1answer
45 views

Predicting whether house is sold: regression or classification

I am new to machine learning (I am currently following the Udemy course machine learning from A-Z). Basically, I would like to reproduce the following analysis (https://www.datasciencecentral.com/...
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2answers
50 views

Unsupervised Learning: Train Test division

I have one conceptual question. In Unsupervised Learning, when I have no labels. The anomaly detection model (Isolation forests, Autoencoders, Distance-based methods etc.), it should fit on a ...
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0answers
15 views

Speed up Conditional Variable Importance for Random Forests

I have trained a random forest in R and now I'm calculating the variable importance mesaure unsing the party Package. ...
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1answer
23 views

AUC ROC when one class consists of smaller subclasses

This question is different from Binary classification when one class consists of multiple subclasses I have two classes that I want to distinguish by a supervised learning classifier such as a random ...
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1answer
31 views

how to resolve skewness problem in regression

I'm working on a regression problem. The dependant variable is skewed and has a distribution as below I'm applying the log transformation but the resulting data is also skewed and is like below. ...
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1answer
37 views

Number of all possible splits in each node of trees in a Random Forest

The trees in a Random Forest are grown by recursive splitting the nodes, and the best split in each node is obtained by using the Gini index, I want to know if there is a possibility to know the ...
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0answers
31 views

Using Random Forest for Optimisation

Can random forests be used for optimisation? I created a random forest which predicts prices, customers will pay. Lets assume I want to maximize the price a customer will pay. To do this I have 3 ...
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1answer
105 views

How much of a problem are autocorrelated residuals of a binary GAM (Generalized Additive model)?

I'm trying to predict high or low crime rate in municipalities (binary 1/0 response variable) using a range of socioeconomic variables. Im doing this with a panel dataset with 300 municipality over 17 ...
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1answer
31 views

What is the industry standard way for determining feature “importance”?

My understanding is, there are different tests to run such as ANOVA, Pearson's Correlation, Chi-Square. Choosing these tests is dependent on if the features / responses are categorial / continuous. ...
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1answer
128 views

Feature Importance in Isolation Forest

In an unsupervised setting for higher-dimensional data (e.g. 10 variables (numerical and categorical), 5000 samples, ratio of anomalies likely 1% or below but unknown) I am able to fit the isolation ...
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4answers
145 views

Why not Always Random Forest in Place of Linear or Logistic Regression

Why Don't we use Random Forest always in place of Linear or Logistic Regressions. When will Linear and Logistic out perform Random Forest.
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0answers
24 views

What does a high GINI in a random forest model imply?

I ran a classification problem using random forest to predict whether a customer will have more than zero revenue in the next 12 months. I am getting a gini of 95 and accuracy of 90% as well. I know ...
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1answer
33 views

Distribution of variable importance in r party package [closed]

I have a dataset of 14558 rows and 250 variables. I am trying to solve a classification problem thanks to r party package and the cforest function (which corresponds to a Random Forest). I would like ...
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1answer
74 views

Random forest permutation test: Is permutation of the training set appropriate?

I have a rather high-dimensional data set (p > 1000) with several variables ranking significantly higher than the rest in terms of variable importance (measured by Gini impurity). However, these ...
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1answer
12 views

Why are there differences in recall values when I use GridSearchCV vs classification_report (scikit-learn)?

I'm currently working on a clasification problem through random forest. When I use GridSearchCV, using the parameter scoring="recall", the best_estimator_ is: ...
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2answers
38 views

how (logistic regression, random forest) deal with input zero values?

I am new in ML. In my dataset there are 11 of 21 features that have some zero values. what is the impact of having zero values as input when using logistic regression or random forest to train my ...
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1answer
62 views

Mean Absolute Error in Random Forest Regression

I am new to the whole ML scene and am trying to resolve the Allstate Kaggle challenge to get a better feeling for the Random Forest Regression technique. The challenge is evaluated based on the MAE ...
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0answers
27 views

In which cases would AdaBoost outperform Random Forest?

I have heard people claim (for example in the course Intro to machine learning , lesson 5) that they like the adaboost algorithm without really providing the reason for why. At the same time, i have ...
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1answer
19 views

mobForest R Package and Model Based Random Forest

I have two covariates and I am using them to predict the response variable using Mobforest_analysis. After prediction, is there a way I can obtain the regression coefficients for both variables along ...
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0answers
33 views

Reducing Bias from a Random Forest - Feature Importance

I'm currently looking to show which of three variables is more important in classifying something as True or False. Everyone agrees that all three variables are important, but not all agreeing on what ...
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0answers
17 views

big difference between r squared in training and test data

I'm building a random forrest regression tree and use cross_validate function from scikit-learn with cv=3 I'm getting a huge ...
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1answer
132 views

Random forest - Out-of-bag estimates

I am reading the chapter on random forests by Leo Breiman (found here: https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf). In section 3.1 Using out-of-bag estimates to monitor error, ...
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0answers
20 views

Applying boosting to predictions from a Random Forest

I have a class of datasets for a binary classification problem where it is known that Random Forest performs poorly compared with GBM or FFNN, rarely adding anything to an ensemble. I've had an idea ...
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0answers
19 views

Can Random Forest predict/assign obs. to each class with the same weight as the weight in training sample?

Assume that I have 5 classes and they are imbalanced. Those classes have weights like 10%, 20%, 40%, 20%, 10% I have more than 100 predictors to do the prediction. Can I somehow ask random forest ...