Results 201 to 210 of about 115,636 (253)

Classification and regression using augmented trees

International Journal of Data Science and Analytics, 2018
In this work, we present an algorithm for regression and classification tasks on big datasets using augmented tree models. Partitioning a big dataset using a tree model permits us to apply a divide and conquer strategy to classification and regression tasks.
Rajiv Sambasivan, Sourish Das
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Classification and regression

Tutorial notes of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, 1999
With over 800 million pages covering most areas of human endeavor, the World-wide Web is a fertile ground for data mining research to make a difference to the effectiveness of information search. Today, Web surfers access the Web through two dominant interfaces clicking on hyperlinks and searching via keyword queries This process is often tentative and
Johannes Gehrke, Wei-Yin Loh, Raghu Ramakrishnan 0001   +2 more
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Regression and Classification Trees

2012
Regression trees and classification trees are suggested as tools to be able to assess the appropriateness of covariates and factors, together with their interactions for linear models. The use of regression and classification trees is demonstrated using the same example dataset as was used in Chap. 15.
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Classification and Regression Trees

2005
It is the goal of classification and regression to build a data-mining model that can be used for prediction. To construct such a model, we are given a set of training records, each having several attributes. These attributes either can be numerical (e.g., age or salary) or categorical (e.g., profession or gender).
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Optimal partitioning for classification and regression trees

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991
An iterative algorithm that finds a locally optimal partition for an arbitrary loss function, in time linear in N for each iteration is presented. The algorithm is a K-means-like clustering algorithm that uses as its distance measure a generalization of Kullback's information divergence.
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Classification and regression trees for bone marrow immunophenotyping

Cytometry, 1995
AbstractMethods are needed to assist with automating three‐color flow cytometric immunophenotyping of bone marrow from leukemia patients. Described is a method in which a normal bone marrow data set is used as a template against which to compare leukemic bone marrow data sets.
R J, Beckman, G C, Salzman, C C, Stewart
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Classification And Regression Trees

Nature Methods, 2017
Leo Breiman, J. H. Friedman, Richard A. Olshen, C. J. Stone   +3 more
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Classification and Regression Trees

2023
Luiz Paulo Fávero, Patrícia Belfiore, Rafael de Freitas Souza   +2 more
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Using Classification and Regression Trees

2018
Classification and regression trees (CART) is one of the several contemporary statistical techniques with good promise for research in many academic fields. There are very few books on CART, especially on applied CART.This book, as a good practical primer with a focus on applications, introduces the relatively new statistical technique of CART as a ...
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Classification and Regression Trees (CART)

2008
In this chapter, we consider tree structures as part of a further transition from conventional regression to statistical learning. Classification and Regression Trees (CART) is emphasized. Tree structures are less important as stand-alone data analysis procedures than in the past.
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