Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation
Train the ensemble of optimal trees for classification.
Optimal Trees Ensembles for Regression, Classification and Class Membe...
Train the ensemble of optimal trees for class membership probability e...
Train the ensemble of optimal trees for regression.
Prediction function for the object returned by OTClass
Prediction function for the object returned by OTProb
Prediction function for the object returned by OTReg
Functions for creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019). (2019) <doi:10.1007/s11634-019-00364-9>) and class membership probability estimation (Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, A, Adler, W & Lausen, B (2016) <doi:10.1007/978-3-319-25226-1_34>) are given. A few trees are selected from an initial set of trees grown by random forest for the ensemble on the basis of their individual and collective performance. Three different methods of tree selection for the case of classification are given. The prediction functions return estimates of the test responses and their class membership probabilities. Unexplained variations, error rates, confusion matrix, Brier scores, etc. are also returned for the test data.