نتایج جستجو برای: derived from regression tree
تعداد نتایج: 5991938 فیلتر نتایج به سال:
Abstract Machine learning (ML) has powerful nonlinear processing and multivariate capabilities, so it been widely utilised in the fatigue field. However, most ML methods are inexplicable black-box models that difficult to apply engineering practice. Symbolic regression (SR) is an interpretable machine method for determining optimal fitting equation datasets. In this study, domain knowledge-guid...
A classification or regression tree is a prediction model that can be represented as a decision tree. This article discusses the C4.5, CART, CRUISE, GUIDE, and QUEST methods in terms of their algorithms, features, properties, and performance.
Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependen...
Decision trees, either classification or regression trees, are especially attractive type of models for three main reasons. First, they have an intuitive representation, the resulting model is easy to understand and assimilate by humans [BFOS84]. Second, the decision trees are nonparametric models, no intervention being required from the user, and thus they are very suited for exploratory knowl...
The study was done to predict egg weight from the external traits of Guinea fowl using statistical methods multiple linear regression (MLR) and tree analysis (RTA). A total 110 eggs a flock 23-week-old were evaluated. Egg (EW) traits: eggshell (ESW), polar diameter (EPD), equatorial (EED), shape index (ESI), surface area (ESA) measured. Descriptive statistics, Pearson correlation coefficients, ...
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