Questions tagged [random-forest]

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.

Filter by
Sorted by
Tagged with
3
votes
1answer
46 views

scikit-learn RandomForestClassifier always hits 100% test accuracy

I have been playing with a toy problem to compare the performance and behavior of several scikit-learn classifiers. Brief, I have one continuous variable X (which contains two samples of size N, each ...
0
votes
0answers
7 views

Negative correlation between OOB statistics and test set statistics during tuning of a RandomForest

I am tuning the parameters of a binary random forest classifier using a random search with a priority queue for training. After training with a fixed number of estimators (3000), the strategy is to ...
0
votes
0answers
17 views

Identify and correct mislabeled categorical data in supervised learning

I have game/player level football data in 230 dimensions and want to classify the likely position that each player was playing in each match. The data is labelled, however each player is classified ...
5
votes
1answer
259 views

Boosting with highly correlated features

I have a conceptual question. My understanding is, that Random Forest can be applied even when features are (highly) correlated. This is because with bagging, the influence of few highly correlated ...
1
vote
1answer
7 views

How can I tell whether my Random-Forest model is overfitting?

I was trying to generate predictions for Iris species using the UCI Machine Learning Iris dataset. I used a RandomForestClassifier with GridSearchCV and calculated the mean absolute error. However, ...
0
votes
0answers
13 views

factors in the success of startup fundraising

I have been following this paper published in 2019. There are few things that are ambiguous and not at all clearly explained. On page 7, table 2, Max Portfolio, ...
0
votes
1answer
29 views

Dicsrete values as taget variable

I have discrete values in the target variable(Exactly 13 different values in total) . When I am giving that as input to Random forest Classifier ,it gives error that input as continuous. And if I give ...
1
vote
1answer
20 views

GridSearchCV using Random Forest Reg Pipeline

...
1
vote
1answer
31 views

using feature selection to improve model performance

I have a highly sparse dataset that I am using to predict a continuous variable via a random forest regression. I have achieved an acceptable level of performance following cross-validation, and I am ...
1
vote
1answer
11 views

Find the optimal n_estimator by looping the model accuracy indicator in random forest algorithm - python

i'm trying to find the best n_estimator value on a Random Forest ML model by running this loop: ...
1
vote
0answers
39 views

Understanding the output of the Random Forest method for classification

I'm using a Random Forest method to predict the behavior of failures at Period_12. My dataset has information about the eleven periods before, considering 112 subperiods (rows). Each one of these ...
2
votes
1answer
15 views

How do we determine what is learnt by a ML model?

I am trying to investigate/justify the output of a random forest regression model for a financial problem, where justification of the output is also important. In that context, for the random forest ...
0
votes
1answer
28 views

What is the selection criteria to choose between XGBoost and Random Forest

I am trying to understand - when would someone choose Random Forest over XGBoost and vice versa. All the articles out there highlights on the differences between both. I understand them. But when ...
1
vote
1answer
62 views

Recommendations for statistical models given my dataset

I'm having a problem when using the k-fold cross-validation with the Random Forest method. One of the outputs is the error "Error in randomForest.default(x, y, mtry = param$mtry, ...) : Need at least ...
0
votes
1answer
20 views

Dissecting performance issues with Random Forest

My task is to identify potential situation for trading and determine whether a candidate is going to succeed or not. I have a system in place to identify candidates, but there is a high rate of false ...
1
vote
2answers
43 views

How to apply model to training data to identify mislabeled observations?

I have a list of people, attributes about those people (height, weight, blood pressure, etc.), and a binary target variable called has_heart_issues. This data ...
3
votes
0answers
17 views

Serializing a trained classification model into a set of actionable insights

I'm looking for ways to convert a trained classification model into a list of insights based on the resulting parameters of the model. To make an example, let's assume we trained a decision tree to ...
2
votes
0answers
23 views

Random forest mode scoring

We are using random forest algorithm but having some trouble understanding the scoring method it uses. take for example the following CM of the test set: ...
0
votes
0answers
24 views

Using numpy array as a feature in RandomForestClassifier

I am working on a bit of a variant to the standard image based object detection problem. “Standard” implying passing a trained model an image, and getting back bounding boxes, scores,…etc for all ...
0
votes
3answers
30 views

Random Forest Target/prediction maximum minimum

This is my current situation, I currently have a regression random forest that is targeting a continuous variable (sales amount) is there any configuration for the classifier that allowed me to set a ...
0
votes
0answers
13 views

Physical interpretation of contribution of a feature in regression

I have built a random forest regression model for credit underwriting. But the business doesn't appreciate a black-box approach. So, using treeinterpreter, I have ...
3
votes
0answers
69 views

Is my model over fitting or not?

I have 50000 observations with 70% positive and 30% negative target variable. I'm getting accuracy of around 96-99% which seems unreal of course and I'm worried that my model is over-fitting which I ...
1
vote
1answer
35 views

Weka: Implementation of Random Forest

I am wondering how random forests are exactly implemented in Weka. This paper is very specific about RFs in Weka, but the description of its learning process in chapter 2 seems strange to me. They say:...
2
votes
0answers
17 views

Logic Check: Building a SKLearn Pipeline

I am new to the concept of building a pipeline in SKLearn and would appreciate some sense-checking to ensure that I am not leaking info from my training sets into my test set. Background: I have a ...
2
votes
1answer
39 views

Random Forest workflow?

I have a data-set comprised of a fairly large number of columns (over 1000) relative to the number of rows (370) that I am currently running a random forest regression on. I am a little confused with ...
1
vote
0answers
13 views

What toolbox to use to create multi-output random forest(reggression) with custom spltting function at each node?

I am trying to implement "Real Time Head Pose Estimation fromConsumer Depth Cameras" by Fanelli et al. I need to train a random forest(regression) with the following criterion The predicted output is ...
1
vote
1answer
23 views

Which decision tree model is used in “standard” random forest?

Is that CART? Why not using C5.0 tree? A perhaps more general question: Since C5.0 tree frequently have better performance than CART, why people still use CART to build random forest (or people ...
1
vote
2answers
61 views

is it ok to get 100% accuracy in random forest classifier algorithm?

while i was building the model to predict the performance of machine using the features like OEF,working time,performance/head etc... I splitted the training data using ...
1
vote
1answer
17 views

is there any rule to apply pca to the imbalance data? [closed]

Is there any rule to apply PCA to imbalanced data? (randomforest, xgboost) I used multiclass imbalance data to pca but the log-loss accuracy getting decrease any theoritical background of this?
-1
votes
1answer
26 views

random forest and log_loss metric?

Light gbm has the metric with log_loss for binary or multi classification. is Random Forest also has the loss function with log_loss?
0
votes
1answer
14 views

when my RF log_loss socre is different then submit score?

I train the RF and I sumbit to the data competition but my train score is so much different then their submit socre is there way to decrease this gap? Here is my code with RF ...
1
vote
1answer
31 views

order of features for model tuning vs model fitting

Assuming that the same columns (i.e., features) are used for hyperparameter tuning and model fitting, and ensemble models are used for modeling (e.g., Random forest or XGboost), then does the order of ...
0
votes
0answers
14 views

box plot and the anomaly detection?

i'm doing a classification problem with 50000 rows × 5000 columns of dataset. calssification label is 300 labels 1. This is the few example of box plot of some feature. what can I inference from ...
1
vote
0answers
13 views

Do you need to perform variables reduction for tree-based models?

I know for methods and linear regression, GLM, Logistic regression, we typically run through a lot of variable reduction methods, i.e, forward/backward/stepwise, univariate analysis; variable ...
5
votes
1answer
107 views

Why gradient boosting uses sampling without replacement?

In Random Forest each tree is built selecting a sample with replacement (bootstrap). And I assumed that Gradient Boosting's trees were selected with the same sampling technique. (@BenReiniger ...
0
votes
0answers
41 views

Keras : How to Connect CNN ResNet50 with svm/random forest classifier?

I want to classify multiclass (10 classes) images with random forest and SVM classifier, that is, make a hybrid model with ResNet+SVM , ResNet+random forest. My ResNet code is below: ...
1
vote
1answer
25 views

LIME Random Forest explanations:

I'm using LIME to explain my random forest model. Everything is working great. However, I don't quite understand the image that is generated. Taking the example from the Readme: How can it predict ...
-1
votes
2answers
35 views

Techniques for increase random forest classifier accuracy

I build basic model for random forest for predict a class. below mention code which i used. ...
1
vote
0answers
14 views

Multiclass AUC score higher than binary

I just built a random forest classifier and wondered about the results. I have 4 classes: A, B, C and control. When I compare A vs control, B vs control, C vs control I get a lower average AUC score ...
0
votes
1answer
24 views

imbalanced target dataset(multi class)

I have a multi-class prediction problem but the 300classes is imbalanced should I make it balance all 300 class will predict the better result? is there an easier method to do this job? if I'm using ...
0
votes
1answer
140 views

Feature Importance from a GridSearchCV

I created a GridSearchCV for a Random Forest Regressor. Now i want to check the feature importance. I searched around and I found this ...
5
votes
1answer
43 views

Search for hyperparameters whith different features using Random Forest

I have a dataset in which I would like to perform a classification model, so I have decided to use Random Forest. The number of features that I have is approximately 200 and I would like to test which ...
2
votes
0answers
35 views

Confused about the MSE ERROR

I am created a random forest regressor and calculate my own error. I want also to calculate MAE, MSE and RMSE to compare my results to similar usecases. But the results of the MAE, MSE, RMSE are ...
1
vote
2answers
29 views

How many trees does a random forest need?

At first, I did a GridsearchCV and the best parameter is a random forest with just 100 trees. My trainset has 80.000 rows and 669 columns. My test set has 20.000 rows and 669 columns. How is it ...
4
votes
2answers
64 views

It is alright to split a GridSearchCV?

Is it ok to split a GridsearchCV? At first, I would try estimators from 100 - 300 (100 steps) for a random forest regressor and some other parameters and after that GridsearchCV I would start the ...
2
votes
1answer
32 views

Why does my GridSearcCV always break up?

My GridSearchCV for my random forest breaks up. I need to know the reason and the solution to make it work: ...
2
votes
1answer
40 views

Bagging or Random Subspace Method for Random Forest?

I am reading a lot about the random forest regressor. I reading about bagging (bootstrap and aggregation) and random subspace. But I am not sure if the random forest regressor just using bagging or ...
2
votes
1answer
34 views

Should I transform my feature into normal distrubition before Isolation Forest

I have a anomaly detection problem and my features are following exponential distrubition. Should I first transform my features into normal distrubition before feed into isolation forest?
3
votes
1answer
49 views

Make a random forest estimator the exact same of a decision tree

The idea is to make one of the trees of a Random Forest, to be built exactly equal to a Decision Tree. First, we load all libraries, fit a decision tree and plot it. ...
0
votes
1answer
84 views

How many features does (Random Forest) need for the trees? [closed]

How can I determine how many features Random Forest needs to create a tree?

1
2 3 4 5
11