Classification and regression trees breiman pdf download

View 4 excerpts, cites background and methods. Classification, which is the task of assigning objects to one of several predefined categories, is a pervasive problem that encompasses many diverse applications. Examples include detecting spam … Expand.

The use of classification and regression trees in clinical epidemiology. View 5 excerpts, cites background. Randomization in Aggregated Classification Trees. Using Model Trees for Classification. View 3 excerpts, cites methods. Induction over large data bases. Techniques for discovering rules by induction from large collections of instances are developed. These are based on an iterative scheme for dividing the instances into two sets, only one of which … Expand. Efficient decision tree design for discrete variable pattern recognition problems.

Application of information theory to the construction of efficient decision trees. View 1 excerpt, references background. Identification Keys and Diagnostic Tables: a Review. Professor E. Pattern classification and scene analysis. Abstract We consider regression situations for which the response variable is dichotomous. The most common analysis fits successively richer linear logistic models and measures the residual variation … Expand.

Some methods for classification and analysis of multivariate observations. The main purpose of this paper is to describe a process for partitioning an N-dimensional population into k sets on the basis of a sample.

The process, which is called 'k-means,' appears to give … Expand. View 1 excerpt, references methods. George, and R. Bayesian CART model search with discussion. Journal of the American Statistical Association, —, Cho and S. Median regression tree for analysis of censored survival data. Computational Statistics and Data Analysis, —78, Cover and P.

Nearest neighbor pattern classification. Denison, B. Mallick, and A. Biometrika, 85 2 —, Doksum, S. Tang, and K. Journal of the American Statistical Association, : —, Fielding and C. Binary segmentation in survey analy- sis with particular reference to AID.

The Statistician, —28, The use of multiple measurements in taxonomic problems. Annals of Eugenics, —, Hothorn, K.

Hornik, and A. Unbiased recursive partitioning: A condi- tional inference framework. Journal of Computational and Graphical Statistics, 15 3 —, An exhalent problem for teaching statis- tics.

Journal of Statistics Education, 13 2 , An exploratory technique for investigating large quantities of cate- gorical data. Applied Statistics, , Kim and W.

Classification trees with unbiased multiway splits. Jour- nal of the American Statistical Association, —, Classification trees with bivariate linear discriminant node models. Kim, W. Loh, Y. Shih, and P. Visualizable and interpretable regression models with good prediction power. IIE Transactions, , Lim, W. Loh, and Y. A comparison of prediction accuracy, com- plexity, and training time of thirty-three old and new classification algorithms.

LeBlanc and J. Relative risk trees for censored survival data. Bio- metrics, 48 2 —, Journal of Statistics Education, 1 1 , Regression trees with unbiased variable selection and interaction detection. Statistica Sinica, —, Logistic regression tree analysis. In Handbook of Engineering Statis- tics, H. Pham ed. Regression tree models for designed experiments. Second E. In Handbook of Data Visualization, C.

Chen, W. Hardle, and A. Unwin eds. Improving the precision of classification trees. Annals of Applied Statistics, —, Loh, C. Chen and W. Extrapolation errors in linear model trees.

Loh and Y. Split selection methods for classification trees. Sta- tistica Sinica, —, Loh and N. Tree-structured classification via generalized discriminant analysis with discussion. Journal of the American Statistical As- sociation, —, Messenger and L.

A modal search technique for predictive nominal scale multivariate analysis. Morgan and J. Problems in the analysis of survey data, and a proposal.

Learning with continuous classes. Morgan Kaufmann, San Mateo, Fundamentals of Biostatistics, 5th edition. Duxbury, Pacific Grove, Regression trees for censored data. Biometrics, —47, Su, M.

Wang, and J. Maximum likelihood regression trees. Therneau and B. R port by B. R package version 3. Witten and E. Morgan Kaufmann, San Francisco, Further Reading E. Related Papers. By Zhe Zhang. By Wei-yin Loh. Mining event histories: a social science perspective. The models are obtained by Find, read The next four paragraphs are from the book by Breiman et. Classification and Regression Trees. Pacific Grove, CA: Wadsworth. Upload a Thing!

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