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maximization of log-likelihood with Cp, AIC, and BIC penalties, bootstrap and cross-validation error estimation, and coefficient …
Persistent link: https://www.econbiz.de/10005459170
problem, we proposed balanced gradient boosting (BalaBoost) which reformulates gradient boosting to avoid the overfitting to … outperformed the representative supervised learning algorithms, i.e., gradient boosting, Random Forests and Support Vector Machine …
Persistent link: https://www.econbiz.de/10005046618
-of-the-art classification methods. Moreover, a boosting algorithm is applied to this classification method. In addition, a simple procedure to …
Persistent link: https://www.econbiz.de/10005046627
-of-the-art classification methods. Moreover, a boosting algorithm is applied to this classification method. In addition, a simple procedure to …
Persistent link: https://www.econbiz.de/10005246497
We propose a heuristic approach to the detection of evidence for recombination and gene conversion in multiple DNA sequence alignments. The proposed method consists of two stages. In the first stage, a sliding window is moved along the DNA sequence alignment, and phylogenetic trees are sampled...
Persistent link: https://www.econbiz.de/10005459153
The evolution of drug resistance in HIV is characterized by the accumulation of resistance-associated mutations in the HIV genome. Mutagenetic trees, a family of restricted Bayesian tree models, have been applied to infer the order and rate of occurrence of these mutations. Understanding and...
Persistent link: https://www.econbiz.de/10005046581
van der Laan and Dudoit (2003) provide a road map for estimation and performance assessment where a parameter of interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using a loss function. After briefly reviewing this approach, this...
Persistent link: https://www.econbiz.de/10005046582
Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the...
Persistent link: https://www.econbiz.de/10005046590
Statistical inference of graphical models has become an important tool in the reconstruction of biological networks of the type which model, for example, gene regulatory interactions. In particular, the construction of a score-based Bayesian posterior density over the space of models provides an...
Persistent link: https://www.econbiz.de/10005585069
van der Laan and Dudoit (2003) provide a road map for estimation and performance assessment where a parameter of interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using a loss function. After briefly reviewing this approach, this...
Persistent link: https://www.econbiz.de/10005585079