Questions tagged [random-forest]
Random forest is a machine-learning method based on combining the outputs of many decision trees.
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How Random Forest handle missing value in sk-learn? [duplicate]
What is the technic used in Random Forest Regressor from scikit-learn to handle missing value ?
First I thought that a Random Forest regressor was able to natively handle missing value during training ...
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Can I use simulated data only for testing a Random Forest regression already trained on real data?
I am working, using Python, on a Random Forest Regression for the prediction of a target variable. I have trained it and tested it on real data, obtaining satisfying results. Now, I would like to ...
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Feature selection for logistic regression and random forest (using Orange - no coding)
I’m using Orange to create a prediction model for the Indian liver patient dataset (binary target variable – either has or does not have liver disease – with 580 instances and 10 features). I’m using ...
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Why RandomForestRegressor.score() return a coefficient of determination? [duplicate]
In ScikitLearn's method RandomForestRegressor.score(X, y), the coefficient of determination R_2 is returned as a metric of the ...
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Kfold cross val in Regression model
How to use K-fold CV to evaluate my regression model performance to calculate the R2, MAE and MSE in the train set to make the model more robust? This code below refers to the tuned model and I'm ...
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how to train and hypertune a model
As I am new to machine learning, and learning it myself, pardon me if I ask a silly question. My question is: What is the correct approach to building a model for, say, random forest and tuning ...
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If R2 is not appropriate for non-linear ML algorithms such as Random Forests, can a Pearson or Spearman correlation be used as performance metric?
$R^2$ is not appropriate for non-linear models, such as Random Forest (RFs) models.
https://arxiv.org/pdf/1611.03063
Is R-squared truly an invalid metric for non-linear models?
https://...
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Is duplicating dataset an augmentation?
For a very small dataset, there is a lot of overfit in the random forest regressor model. I have removed extraneous data, scaling and feature selection, but overfit is still there. The oversampling ...
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Fixed-effect trained model inspection in mixed-effects random forest (MERF)
I have run a Mixed-Effects Random Forest (MERF) using the python merf module, see therein example use here (see also blog post).
I have read the above and also Hajjem et al's paper, to get an idea of ...
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Significant performance drop between train and validation set
I am trying both Lgbm and RandomForest for a classification, and I observe the same problem. I am using various metaparams to prevent overfitting, such as max_depth, num_trees (keeping it small for ...
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Enforcing symmetries "for bag-of-vector" data in XGBoost or random forest - geodata example for illustration
I'll give a concrete toy problem, then give some comments on what sorts of abstractions I care about.
Toy problem: Each person $i$ in my dataset has a phone, and every once in a while the phone will ...
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What is the difference between model\$pred and model\$finalModel\$votes in a random forest model trained by caret?
I trained a random forest model as below:
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Overfitting in randomForest model in R, WHY?
I am trying to train a Random Forest model in R for sentiment analysis. The model works with tf-idf matrix and learns from it how to classify a review, in positive or negative.
Positive ones are ...
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How do I interpret a Random Forest Survival C-index value relative to the Requested performance error?
I'm doing a random forest survival analysis for a school project and I'm confused about the C-index output that I'm getting relative to the Requested performance error. Shouldn't my C-index get higher ...
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Causal forests for causal interaction effects between two treatment factors
I'm analyzing a survey experiment data with a factorial design with $2 \times 2$, where each factor is randomly assigned with equal probability.
I'd also like to know the heterogeneous effect of the ...
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