All Questions
Tagged with scikit-learnrandom-forest
181 questions
2votes
0answers
9views
Low Accurecy from Geospatial Random forest ML modeling problem - Training Exported from qGIS, SCP
I am doing a geospatial assessment integrated with ML modeling. The problem is the very low accuracy percentage, as more training features increases, it gets lower. What could be he solution to such a ...
- 21
-1votes
0answers
37views
ML model for Career Prediction
I am NOT able to figure out how to make a ML model. I have been chatgpting most of it and understanding the code, I'm doing next to nothing. No matter what code I input, the accuracy is always 0%... ...
0votes
0answers
23views
What happens if one uses the forest-based predictive models with a single tree or estimator for 1D time data?
I'm experimenting conformal prediction over high-frequent time data using following forest-based regression models for an in-sample forecasting task The size of uni-variate (1D) time-series data is <...
- 527
2votes
2answers
142views
Random Forest always predicting the majority class
I'm predicting disease outcome using biological data (metabolites plus covariates age, sex and BMI). The outcome is a binary variable and moderately imbalanced (~12% positive cases). I have a ...
- 31
0votes
0answers
80views
Why is my random forest regressor more likely to under-predict when making larger predictions?
I've recently built my first regression model, using scikit-learn's random forest regressor. The predictions are rounded into one of 12 segments; these begin at £15 and progress in £5 increments up to ...
- 101
1vote
0answers
102views
Interpreting the SHAP values presented in layered violin plot in SHAP-library for Scikit binary RandomForestClassifier
I am using the SHAP-library for computing feature Shapley values for a binary RandomForestClassifier which has naturally two outputs, 0 or 1. The forest itself consists from 100 decision tree ...
- 111
1vote
2answers
257views
Why do we need hyperparameter tuning in Scikit learn? Doesn't sk learn models by default give best model?
When I have the option to build a classifier like this directly clf = RandomForestClassifier() why do we perform tuning by restricting the parameters like this <...
- 13
1vote
0answers
38views
How to know which rules were applied to predict one sample in trained decision tree model?
I have trained Random Forest Regressor from sklearn. I am able to return text representation from each Decision Tree rule using tree.export_text (sklearn documentation here). But it shows rules for ...
- 15
0votes
1answer
367views
Do prediction intervals for Random Forest predictions are average of prediction intervals of trees being Random Forest estimators?
I am working on adding prediction intervals for each prediction value of new input samples. Do prediction intervals for Random Forest predictions are average of prediction intervals of trees being ...
- 15
0votes
1answer
209views
Does Random Forest Regressor use subset of trees to predict value from given data sample?
I will try to draw a little context to my question from title. I build a Random Forest Regressor from 1000 trees using sklearn. Then I exported all the decision paths along with predicted values for ...
- 15
0votes
1answer
232views
Struggling with understanding RandomForest model with SMOTE
From what I understand my code is telling me that my base model is performing at 96% on it's training data, 55% on it's test data. And my SMOTE model is performing at ~96% on both. From my ...
1vote
0answers
251views
Sklearn predicts different results depending on the input length
Here is the problem: I fitted a Random Forest Classifier and saved it to a pickle file. However, when I predict with the entire dataset I get one result, and when run predict line by line (loop) I get ...
- 11
0votes
1answer
38views
How can I be more certain that I have not accidentally made my ML model predict on training data?
I have this random forest model setup as shown below in python. It's performing unexpectedly well with a ~70% classification success rate (to the extent where I really doubt it is genuine) and I am ...
- 11
2votes
1answer
356views
Surrogate splits in Python
I want to use RandomForestClassifier from Sklearn to predict categorical variable (credit risk). But one of the predictors seems to have missing values: ...
- 81
1vote
2answers
22views
Random Forest with less samples & variation in test_scores
I'm building a RandomForestRegressor with 75 samples. The distribution of y (After train_test_split) is as below. (Blue-Train and Red-Test) Keeping test_size=0.3 (...
- 143
