In this study, we reanalyzed our previous data and developed a new decision tree
model using simple and basic parameters included in community health records.
To address these issues, we propose an information fusion model for bearing fault diagnosis by combining the LVQ neural network and the decision tree
classifier, of which the predictions are fused using the DS evidence theory.
The paper is structured as follows: Problem Formulation presented in section 2; Decision Tree
Algorithm for optimal placement and sizing of PV systems presented in section 3; Losses estimation by Decision Tree
Algorithm presented in section 4, Application of Decision Tree
Algorithm in Distribution system and comparison results presented in section 5; and Conclusions of this paper are summarized in section 6.
The image reuse decision tree
went live on the library website on February 17, 2017, and the room reservation wizard went live on August 27, 2017.
A predictive technique like decision tree
can be used in classification, clustering and predictive task.
"Optimizing Pin-in-Paste Technology Using Gradient Boosted Decision Trees
A similar number of cases was correctly classified by the decision tree
model and the composite score approach; the decision tree
model was superior in classifying cases with sunburn (44.3 versus 25.9 percent correctly classified).
In data mining, decision tree
method has widespread use in many scientific areas, such as agriculture, engineering and industry.
In case of Random Tree, a Decision Tree
was drawn randomly in which each tree got equal chance to occur in the sampling (Wang et al., 2015).
We needed another ten years to develop a satisfactory decision tree
pre-pruning method which required no parameter setting.
Methods such as decision tree
or neural network can work with missing values or nonnormal data (Sarma 2013).