Questions tagged [random-forest]

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

Filter by
Sorted by
Tagged with
0
votes
0answers
12 views

DecisionTreeClassifier performing better than RandomForestClassifier

I am currently working on a supervised learning project with sklearn. According to my experiments I observe DecisionTreeClassifier(DTC) performs better than RandomForestClassifier(RFC), both in term ...
0
votes
0answers
8 views

random forest classifier issue (accuracy = 1)

I would like to use random forest in python to make prediction of a failure motor。 and the dataset is constructed by myself (or plz let me know if you have any suggestions) There're 4 cases.(normal + ...
0
votes
0answers
12 views

In what ways are complex machine learning algorithms different from simpler machine learning approaches? How to select your model

In what ways are complex machine learning algorithms (e.g, random forests or support vector machines) different from simpler machine learning approaches (e.g., LASSO or ridge regression)? Is this ...
0
votes
0answers
19 views

Which Random Forest hyperparameters to tune with Grid Search and which are the best initial hyperparameters values? [duplicate]

I want to use Grid Search for finding optimal hyperpameters for Random Forest. My questions are: Which Random Forest hyperparameters are considered important for tuning? Which initial Random Forest ...
1
vote
1answer
25 views

Do tree methods like gradient boosting predict all iterations at once?

If I'm using a tree method (e.g GBM) and I have a time series hourly data, and I predict my target variable $y$ for the next 48 hours, do my predictions were made all at once, or does the second day ...
0
votes
1answer
17 views

Running SequentialFeatureSelector with tree base model seems to be wrong

I'm little bit confused about the integration of using feature selection (SequentialFeatureSelector with ...
0
votes
0answers
3 views

Comparing ML Performance Across Different Feature Subsets

I am performing a random forest regression on a 700X1000 dataset, where the number of features can be logically split into multiple categories (five to be precise). I am using K-fold to generalize, ...
0
votes
0answers
25 views

Mathematical explanation how Random Forest works

I would need to carefully understand the mathematical background behind the RF prediction. I am not sure if this is the right website to post this question, but I will take the chance. Namely, I am ...
1
vote
0answers
11 views

Model for predicting medical outcomes on longitudinal data? Even with uneven time steps?

I have a dataset that originated from medical claims that has one subject/person on multiple rows, along with when the person visited the doctor, and all the diagnoses the person received during that ...
0
votes
0answers
11 views

Random Forest behaviour with multi output hierarchical dependent variables

I have trained Random forest on multi-output(4) variables in python where each dependent variable is multi-class and variables have hierarchical dependency. I cannot provide the actual details due to ...
1
vote
0answers
11 views

Data preparation for classification models

I am trying to predict user response (binary output 1 or 0) based on several interaction factors. After merging all information by user, my database looks like the table below : ID Interaction_Type ...
0
votes
0answers
18 views

At approximately which point do neural networks generally begin to outperform random forests?

I am new to neural networks but my manager has asked me to look into whether they would be useful from a business standpoint. I am aware that neural networks are generally better for non-tabular data ...
0
votes
0answers
8 views

How to select a comprehensive set of parameters for Hyper-parameter tuning Extra Trees Regressor / Random Forest Regressor

I'm trying to use as much parameters as I can in hyper-parameter tuning of Extra Trees Regressor and Random Forest Regressor, so I'll be sure on the model I'm going to use. The parameters in Extra ...
0
votes
1answer
41 views

Random forest method for survival analysis

I'm doing a survival analysis on a dataset. considering "DV" as outcome var, "T" as time to event or censor, V1 - V6 independent variables. I want to use conventional Coxph ...
0
votes
0answers
7 views

Statistical methods for landcover classification

For example, if I have this dataset where I’m taking per year pland values so the coverage of a habitat per 5x5 modis cell – And for a specific ID, where ID represent each unique 5x5 modis cell (the ...
0
votes
0answers
9 views

Random forest on compound analysis and input data permutation

I am using a random forest model to associate climate variables with a specific type of impact, which is measured as the likelihood of failure (therefore, classification). The choice of random forest ...
1
vote
1answer
32 views

Random Forest Regressor Python - cross validation

I'm training a Random Forest Regressor and I'm evaluating the performances. I have an MSE of 1116 on training and 7850 on the test set, suggesting me overfitting. I would like to understand how to ...
0
votes
1answer
16 views

Getting nan scores from RandomizedSearchCV with Random Forest Classifier

I am trying to tune hyperparameters for a random forest classifier using sklearn's RandomizedSearchCV with 3-fold cross-validation. In the end, 253/1000 of the mean ...
0
votes
0answers
32 views

How MSE works in Random Forest regression?

I want to ask about how MSE works in Random Forest regression. I will tell about what i know so far. Please help me clear my confusion or correct me if i'm wrong. First, i find MSE from the sample ...
4
votes
0answers
53 views

Boruta Algorithm for Logistic Regression?

Is it okay to use a Boruta algorithm to select features for a logistic regression? I read several sources, including the source package as well as this site explaining what Boruta does. My ...
0
votes
1answer
24 views

Is it necessary to retrain a random forest instead of removing trees when comparing accuracy between different numbers of trees?

I have a train data set and a validation set using which I wish to optimize the hyperparameter that is the number of trees in a binary classification random forest (scikit-learn). (As Sycorax ...
2
votes
1answer
30 views

K Fold Cross Validation in Python

I am trying to compare 2 classifying methods (SVC vs Random Forest) in order to do that I am using the cross_val_score function. It is posible to use the same folds in both methods? In order to ...
2
votes
1answer
22 views

Get OOB samples of random forest in sklearn [closed]

In sklearn I oob_score_ gives me the OOB score of a random forest model. This score is calculated by the samples which were left out during RF training. Is there a way to get the individual OOB ...
0
votes
0answers
10 views

Prediction variation by changing a features in Regression Problem

I have trained a Random Forest algorithms for a Regression problem. I have used 4 features for predicting the final output (no time series). The results are really good in the sense that the predicted ...
0
votes
0answers
13 views
0
votes
0answers
11 views

Help with identifying regression model for sequences

Let's say I have a regression task, but features are sequences of "letters", so that the order is important. The set of all possible letters is relatively small. Example: ...
1
vote
1answer
22 views

Does Random Forest Regression or Lasso Regression benefit (in terms of accuracy) from predicting multiple outputs at once?

I'm using Random Forest regression and Lasso regression for the task of predicting multiple outputs. I'm using sklearn.ensemble.RandomForestRegressor and ...
0
votes
1answer
21 views

Random forest on survival data

I should make prediction on survival data, using the random Forest method. My question is: should I follow the same approach as in logistic regression? taking into account only the status variable or ...
1
vote
0answers
38 views

Extreme collinearity for Random Forest?

My data have 450 observations and 2200 predictors that I want to use to train a RF model to classify 4 classes. However, about 2165 of the predictors are very highly correlated to each other. The way ...
0
votes
1answer
27 views

How to calculate Random Forest manually?

I have several questions about the Random Forest algorithm. Is it possible to calculate manually using Random Forest? If we can calculate manually, can you please teach me how can I get this data ...
0
votes
0answers
12 views

If I use the random forest algorithm to determine the importance of variables, do I need cross-validation?

If I use use the random forest algorithm to determine the important predictors among many predictors, but not for the actual out-of-sample predictions do I need cross-validation to tune ...
2
votes
1answer
99 views

Using RandomForest, why does changing my training set by ONE point dramatically affect CV error?

I'm working on a time-series, binary classification dataset, where I'm doing cross validation as a moving window as in the diagram below: So I'll use the first three "shifts" as cross ...
0
votes
1answer
23 views

Using Random Forest vote scores as a matching variable?

I am working on a project where we need to identify good counterfactuals / matches for a binary treatment, which is regressed against a binary outcome. The "treatment" that we seek to study ...
2
votes
1answer
23 views

What is the difference beetwen Random Forest and Random Subspace Method?

Is the only difference that the Random Forest enforces the use of decision trees as a base learner and use bootstrap sampling?
6
votes
1answer
129 views

When a classifier predicting probability should be calibrated?

At scikit-learn website they have a very nice picture showing the need to calibrate [some] classifiers to correct bias in predicted probabilities: And they have a very nice explanation of why one ...
0
votes
1answer
58 views

Random Forest Regression and Overfitting

I did gridsearch with corss-validation on a trainingset to search for best hyperparameters for a Random Forest Regressor. And indeed the best parameterset gives good results in cross-validation (R^2 ~ ...
8
votes
2answers
540 views

Are Random Forests good at detecting interaction terms?

How good random forests actually are at finding interactions between variables? Does adding interaction terms explicitly to the model increase the predictive power of random forests?
1
vote
0answers
16 views

Difficulty in understanding how to include covariates in random forest for timeseries data

I read this tutorial on how to use random forest for forecasting using timeseries data ( https://petolau.github.io/Ensemble-of-trees-for-forecasting-time-series/ ), and I have some difficulties to ...
1
vote
0answers
37 views

Variable importance in random forest regression: scaled or unscaled

If I want to use the original random forest variable importance measure Mean Decrease in Accuracy [1] (which can be the Increase in MSE, for example) when applying random forest regression, should I ...
0
votes
0answers
33 views

Dealing with classes in an imbalanced dataset

I have a dataset of continuous features and 4 classes. The classes counts are 1793, 246, 103 and 102. Adding data is quite difficult now. I've done classification with a random forest on the entire ...
1
vote
0answers
17 views

What is the linear component behind a Mixed Effect Random Forest model?

I am a biologist with interest in statistics so in advance I want to apologize for the simplicity and misunderstanding of my statically (mathematical) assumptions and questions. In a GLMM no matter ...
0
votes
0answers
30 views

obtaining proximity matrix from random forest for unsupervised scenario in R

I recently came across the concept of proximity matrix in random forests (see for example this great StatQuest video). This can easily be obtained in the regression or classification scenario like so: ...
0
votes
0answers
22 views

Why the computational time of random forest is lower than the decision tree?

What I understood is that RF trains many decision trees. RF supposes to have higher training and testing time. Based on my experiments, it seems like RF have a lower computational time. Is this ...
0
votes
0answers
9 views

Can the permutation importance strategy for feature selection be used for time series data?

After having fitted a Random Forest classifier for a binary classification, I want to use the permutation importance strategy for feature selection. However, since this method implies the permutation ...
0
votes
0answers
26 views

Appropriate hypothesis test for comparing 3+ regression models

I'm struggling to locate the exact type of hypothesis test I need. Here is the situation. I have field plots (n > 30,000) which have been established to measure forest attributes. The response of ...
1
vote
3answers
74 views

Regressor overestimates low values and underestimates high values

I have preprocessed the data and trained a regressor (random forest). Then i made a predicted v/s real values plot, to see the model behavior. Here, i noted that the regressor consistenly ...
3
votes
1answer
74 views

How to include the effect of the spatial autocorrelation in random forest algorithm?

I have spatial autocorrelation (SAC) in my observations and I want to use two species distribution models Random forests and logistic regression, I’m planning to include the SAC as an autocovariate «  ...
0
votes
0answers
18 views

Predicting target variable for some a small group of a data by machine learning algorithms

This will be a general question about machine learning. Let say, I have such a data which have such variables: y(target variable): Salary x1: Age x2: Job x3: Location Let say, I want to predict y by ...
0
votes
1answer
42 views

On the existence of rule of thumb for machine learning algorithms

I want to know if there are conditions about the minimum number of observations to have (the relation between the number of variables and the number of presence and absence records) in order to use ...
0
votes
0answers
14 views

How do repeated examples in the bootstrap sample affect building of a random forest?

Random forest algorithm builds many decision trees using bootstrap samples from the original dataset. (Individual trees use only a subset of the features but my question is not related to that). Each ...

1
2 3 4 5
42