query: What is the purpose of using a decision tree?
positive_passages.docid: 22364
positive_passages.text: What is the purpose of using a decision tree?
negative_passages.docid: 67671
negative_passages.text: What is the purpose of class methods?
negative_passages.docid: 59364
negative_passages.text: Why should the data be shuffled for machine learning tasks
negative_passages.docid: 121252
negative_passages.text: Interpreting output of importance of a random forest object in R
negative_passages.docid: 69831
negative_passages.text: Obtaining knowledge from a random forest
negative_passages.docid: 126595
negative_passages.text: Does feature selection help improve the performance of machine learning?
negative_passages.docid: 49421
negative_passages.text: Can a decision in a node of a decision tree be based on comparison between 2 columns of the dataset?
negative_passages.docid: 139415
negative_passages.text: Interpretation of Importance score in Random Forest
negative_passages.docid: 81918
negative_passages.text: Multicollinearity in Decision Tree
negative_passages.docid: 51084
negative_passages.text: Won't highly-correlated variables in random forest distort accuracy and feature-selection?
negative_passages.docid: 50358
negative_passages.text: Choosing Random Forests' parameters
negative_passages.docid: 85385
negative_passages.text: Why do we need multivariate regression (as opposed to a bunch of univariate regressions)?
negative_passages.docid: 51863
negative_passages.text: Logical Conditional Truth Table Rationale
negative_passages.docid: 123307
negative_passages.text: Ideas for outputting a prediction equation for Random Forests
negative_passages.docid: 115455
negative_passages.text: What is the correct way to use train, validation and test set when comparing classifiers?
negative_passages.docid: 69637
negative_passages.text: Random Forests and data transformations
negative_passages.docid: 13076
negative_passages.text: Is random forest a boosting algorithm?