Every node on decision tree has a corresponding sample set. By analyzing the quantity of sample in the sample set or the purity of it, algorithm PDTBS, viz. pre-pruning decision tree based on support, and algor
An implementation of decision tree, with algorihtms for pre-pruning and post-pruning. Only ID3 now. Use graphviz for visualization. - MogicianXD/DecisionTree
resulting in a hydrologic regime that differs significantly from the natural flow regime before the impoundment. For precise planning and judicious use of available water resources for agricultural operations and aquatic habitats, it is critical to assess the dam water’s temperature...
Horticultural practices, such as water management, nutrition, fertilizer application, pruning, and rootstock selection influence citrus rind physiology, like rind color [[19], [20], [21]]. Genetic differences between citrus cultivars result in rind physiology variations due to significant differences ...
One major factor that has been reported to contribute to chronic poverty and malnutrition in rural Haiti is soil infertility. There has been no systematic review of past and present soil interventions in Haiti that could provide lessons for future aid ef
The Construction of Scalable Decision Tree based on Fast Splitting and J-Max Pre-Pruning on Large Datasetsdoi:10.5829/IJE.2021.34.08B.01S. LotfiM. GhasemzadehM. MohsenzadehM. MirzarezaeeMaterials and Energy Research Center
prepruning processDecision tree learning is one of the most widely used machine learning methods. Its two major parts are creating a tree and controlling its size. The advantage of rough set theory for processing uncertain data is used in this paper. From the viewpoint of the certainty of a...
menu auto_awesome_motion View Active Events Md Isaar·1y ago· 54 views arrow_drop_up12 Runtime play_arrow 19s Language Python
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