Questions tagged [cart]
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11
questions
0
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0answers
17 views
How to get variance for regression tree fit?
Suppose the true function is a tree such that:
$$f(x)=\sum_{j=1}^{J}b_j I(x \in R_j)+e_i$$
where $b_j=E(y|x \in R_j)$ ,$E(e_i)=0$ and $R_j$ as terminal node.
Suppose we got a fit for this tree via ...
0
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1answer
35 views
scikit learn target variable reversed (DecisionTreeClassifier)
I created a Decision Tree Classifier using sklearn, defined the target variable:
...
3
votes
2answers
123 views
List of samples that each tree in a random forest is trained on in Scikit-Learn
In Scikit-learn's random forest, you can set bootstrap=True and each tree would select a subset of samples to train on. Is there a way to see which samples are used in each tree?
I went through the ...
1
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0answers
15 views
Looking for CART/ML model that works with relative data [duplicate]
I am a beginner at AI and ML. I have been given a dataset, where I have noticed the columns are relative to one another. So is there any CART or ML model that can work with relative data ?
For example ...
0
votes
1answer
44 views
how are split decisions for observations(not features) made in decision trees
I have read a lot of articles about decision trees, and every one of them only focused on telling how a feature/column is considered for split, based on criterion like gini index, entropy, chi-square ...
1
vote
1answer
24 views
Random selection of variables in each run of python sklearn decision tree (regressio )
When I put random_state = None and run Decision tree for regression in python sklearn, it takes different variables to build tree each time?
Shouldn't there be only ...
1
vote
0answers
36 views
Prediction in CART Decision Trees
I was studying the algorithm of CART (classification and regression trees), but the formula of the prediction is irritating me.
First we have the following definition:
Let $X:={x_1,...,x_N} \subset \...
1
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0answers
32 views
What is the difference between a decision tree and something called "subgroup discovery algorithms"?
I'm reading a paper which states that subgroup discovery is:
...
2
votes
1answer
83 views
Problems with decision tree labeling of nodes
Decision trees as we know assigns label to the node based on majority class voting. I am curious to find that what could be the problems with such labeling schemes? Does it lead to overfitting the ...
1
vote
0answers
27 views
CART classification for imbalanced datasets with R
Hey guys i need your help for a university project. The main Task is to analyze the effects of over/under-smapling on a imbalanced Dataset. But before we can even start with that, our task sheet says, ...
3
votes
1answer
79 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.
...
