Questions tagged [cart]
The cart tag has no usage guidance.
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How to group multiple categories of a categorical variable before feeding the data to a machine learning algorithm?
I have a labelled dataset to which I wish to fit a classification model (say, a Decision Tree). One of the categorical variables (say STATE) in the data has a lot ...
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Simple CART model example
My goal is to test Decision tree to regression model.
My data is like below(python dataframe). There are 2 features F1 and F2. And there is label which is number.
How to make CART model from this ...
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scikit learn target variable reversed (DecisionTreeClassifier)
I created a Decision Tree Classifier using sklearn, defined the target variable:
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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 ...
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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 ...
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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 ...
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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 ...
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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 \...
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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:
...
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139
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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 ...
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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, ...
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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.
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