A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.
Attempting to create a decision tree with cross validation using sklearn and panads. My question is in the code below, …
machine-learning decision-tree cross-validationI've been coding for a few years but I still haven't gotten the hang of pseudo-coding or actually thinking things …
c++ machine-learning decision-tree entropyI am doing research on data mining and more precisely, decision trees. I would like to know if there are …
performance machine-learning complexity-theory classification decision-treeWhen I plotted the decision tree result from ctree() from party package, the font was too big and the box …
r output decision-treeConfused about random_state parameter, not sure why decision tree training needs some randomness. My thoughts, (1) is it related to …
python python-2.7 machine-learning scikit-learn decision-treeI've been reading up on Decision Trees and Cross Validation, and I understand both concepts. However, I'm having trouble understanding …
algorithm machine-learning decision-treeI am attempting to tune an AdaBoost Classifier ("ABT") using a DecisionTreeClassifier ("DTC") as the base_estimator. I would like …
python scikit-learn decision-tree adaboost grid-searchI am using R to classify a data-frame called 'd' containing data structured like below: The data has 576666 rows and …
r machine-learning classification decision-tree rpartI've read from this documentation that : "Class balancing can be done by sampling an equal number of samples from each …
scikit-learn random-forest decision-treeI want to apply a decision tree learning algorithm to a dataset I have imported from a CSV. The problem …
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