What are the advantages of TreeNet® ?
TreeNet® advantages include: • Automatic selection from thousands of candidate predictors • No prior variable selection or data reduction is required • Ability to handle data without preprocessing • Data do not need to be rescaled, transformed, or modified in any way • Resistance to outliers in predictors or the target variable • Automatic handling of missing values • General robustness to dirty and partially inaccurate data • High Speed • Trees are grown quickly; small trees are grown extraordinarily quickly • TreeNet® is able to focus on the data that are not easily predictable as the model evolves • Thus, as additional trees are grown fewer and fewer data needs to be processed • In many cases, TreeNet® is able to train effectively on 20% of the data • Resistance to Over Training • When working with large data bases, even models with 2,000 trees show little evidence of overtraining • Most models show maximum accuracy well before 1,000 trees are grown TreeNet® ‘s robustness extends to
