Questions tagged [random-forests]
For questions related to the random forest (or random decision forests), which is an ensemble machine learning technique (that is, an ML technique that uses or combines different models).
7
questions with no upvoted or accepted answers
2
votes
0
answers
89
views
How can I classify instances into two categories and then into sub-categories, when the number of features is high?
I'm working with a problem where I have a lot of variables for different cases of different users. Depending on the values of the different variables of a concrete user in a concrete case, the ...
1
vote
0
answers
32
views
Derive information for sub-scoring from one scoring model
I am currently working in Python with a random forest algorithm to perform a scoring. My output is binary.
The idea now is to derive sub-scores from the above model that give an opinion on different ...
0
votes
0
answers
11
views
What model is good for learning both within and across categories?
How can I incorporate both general trends and subcategory-specific trends into a model?
Let's say I am predicting factors that affect import volume, for example. There are many industries which have ...
0
votes
0
answers
20
views
Same prediction result with little probabilities change
I built a job prediction system leveraging data scrapped from LinkedIn with Random Forest and compared it to XGBoost. XGBoost was used due to its high accuracy after training.
When I made a prediction,...
0
votes
0
answers
26
views
How to make a RandomForestRegressor learn to differentiatie similar inputs with different outputs?
I'm working on a regression task with Sklearn RandomForestRegressor and I'm having some trouble distinguishing between two similar data with very different expected outputs. For example, each pair of ...
0
votes
0
answers
7
views
How much is the acceptable percentage for Random Forest in Landslides prediction?
RF had been developed to overcome overfitting in decision trees but in some cases RF still experiences overfitting in landslide prediction, which varies from 2% to 12%. How much overfitting is ...
0
votes
1
answer
640
views
Why does GridSearchCV model give worse results despite same parameters used with base model
I am trying to make prediction using random forest regression and then utilize GridSearchCV to tune hyperparameters(just 'n_estimators'). However results of GridSearchCV are worse than base model. ...