An Introduction to Classification and Regression Tree (CART) Analysis

By R. Lewis. 2000

813 citations recorded by the source corpus.

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Citations in the corpus

Modelling invasion for a habitat generalist and a specialist plant species (2008, methodology): “Finally, we tested two commonly employed regression models; logistic regression (Evans et al ., 2000; Pearce & Ferrier, 2000) and classification tree analysis (Breiman et al ., 1984; Lewis, 2000), both of which require presence and absence data.”
Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities (2020, methodology): “To carry out this estimation, several machine learning models and algorithms are available, from the widely used basic linear regression (LR) [20] and polynomial response surface (PRS) [21], to more advanced techniques, such as support vector regression (SVR) [22], decision tree regression (DTR) [23”
Differential Privacy for Deep and Federated Learning: A Survey (2022, methodology): “Afterward, the authors use classiﬁcation and regression tree (CART) [102] to apply DP in function of the relevance/impact of each attribute on the classiﬁcation results.”
Is It Who You Know, or How Many That Counts? Criminal Networks and Cost Avoidance in a Sample of Young Offenders (2010, methodology): “One of the advantages of CHAID is that it is a non-parametric method; it thus performs well with non-linear, highly skewed variables, or those with an ordinal structure (Lewis, 2000), such as the ones considered in the current study.”
Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis. (2005, unknown): “Calcium channel blocker 7560 (23) 7369 (23)”
Depth-images-based pose estimation using regression forests and graphical models (2015, background): “In recent years, some joint 60 detection algorithms using random forests give real-time state-of-the-art re61 sults [29, 30, 31, 32, 33].”
Decreased beta-amyloid1-42 and increased tau levels in cerebrospinal fluid of patients with Alzheimer disease. (2003, methodology): “03-111 [1-42] and catalog No.”
Forecasting Fine-Grained Air Quality Based on Big Data (2015, methodology): “Over the past decade, some statistic models, like linear regression, regression tree [5][9] and neural networks, have been employed in atmospheric science to do a real-time prediction of air quality [4][6] [7][12][13].”
Predicting the Geographical Origin of Music (2014, methodology): “Random forest regression The Random Forest Regression (RFR) method is a process of binary recursive partitioning [15].”