-
Link to repository with potentially good info on decision trees and random forests:
https://github.com/gregtam/interpreting-decision-trees-and-random-forests
I will look at these resources more cl…
-
As far as I can tell, the `loss` parameter is only exposed for single trees. I think this would be pretty easy to add to the ensemble models.
Issue raised at #211.
-
This is another option to reduce the computation time involved in exploring the paths through large random forests. This option would be of particular relevance to random forests with many trees whil…
-
The xgboost, RF and NN models all have different ways to handle imbalanced classification datasets by using class-specific weights in their loss functions; but we currently only support this for NN mo…
-
Goal: Code different clustering algorithms to find clusters within the data. Will use Randomer Forests, MeanShift, and Agglomerative Clustering algorithms. Will use NMF to get features from these clus…
-
Creation of random forests with lstchain_mc_trainpipe with a large training sample takes a long time and a lot of memory. We'd like to train RFs which are valid for a wide range of telescope pointings…
-
Hi
I am following the example for Random Forests : https://pbiecek.github.io/breakDown/articles/break_randomForest.html
I am still not sure how to translate the output of breakDown.
in the example …
-
P-Values for variable importance are desirable as they are easier to interpret and will be potentially easier to drop in to our [other tools](https://github.com/cancerregulome/).
A couple of differen…
-
**Problem Description:**
The current Loan Eligibility Estimator lacks a developed predictive model, which is crucial for assessing loan approvals. Additionally, the existing system may not be consi…
-
spawn from corpses
random starting forests