Topic
Decision tree model
About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.
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01 Jun 2019
TL;DR: This study helped diagnose diabetes by selecting the optimal decision tree model, which is efficient evaluated by confusion matrix, accuracy, specificity and specificity and can achieve better accuracy.
Abstract: Diabetes is one of the fastest growing non-communicable diseases in the world. The reason is that the body's ability to produce or respond to insulin is impaired, leading to abnormal metabolism of carbohydrates and elevated levels of diabetes in the blood and urine. This study helped diagnose diabetes by selecting the optimal decision tree model. In order to prevent overfitting of the decision tree model, Expectation-maximization (EM) clustering algorithm is used for data reduction, and then the data is divided into three data sets. The decision tree model is established by different hyperparameters, then the model with the highest accuracy is selected as the optimal model. The model is efficient evaluated by confusion matrix, accuracy, sensitivity and specificity. Compared with other previous studies mentioned in the literature, the proposed model can achieve better accuracy.
3 citations
01 Jan 2012
TL;DR: The complexity of models and databases plays a pivotal part in model-based research, and in increasing the complexity there is also a larger need for data support, and factors may have been introduced into the model or database of which there is only limited knowledge.
Abstract: The complexity of models and databases plays a pivotal part in model-based research. Simple models and databases contain only few processes and variables, and usually have only limited predictive value. More complex models and databases are aimed at more reliable and more accurate predictions. They contain more processes and variables, describing more details of the modelled system. However, in increasing the complexity there is also a larger need for data support, and factors may have been introduced into the model or database of which there is only limited knowledge. In practice, a significant increase in the complexity may actually increase rather than decrease the uncertainty with regard to the model or database output. Apart from that, several practical issues play a role in the complexity of simulation models and databases, for instance, the running time of more complex models easily outgrows computer capabilities, which reduces the possibilities for rigorous testing, verification, sensitivity analysis, bifurcation analysis, validation and calibration of the model, and thus decreases the confidence in the model [1].
2 citations
21 Nov 2016
TL;DR: A new encoding schemes based on tree representation is represented to encode recurrent multi layer neural network to implement a learning process formed by two iterative phases: structure optimization and parameters optimization.
Abstract: In this paper, a new encoding schemes based on tree representation is represented to encode recurrent multi layer neural network. It implement a learning process formed by two iterative phases: structure optimization and parameters optimization. For the structure evolving, a modified version of the Genetic Programming algorithm was adapted to support the recurrent topology of the network. On the other hand, a hybrid version of Harmony Search algorithm is used to adjust the network parameters including connection weights and neurons parameter set. Besides, the proposed model is evaluated by dynamical chaotic times series and compared with other studies.
2 citations
Patent•
30 Oct 2018
TL;DR: In this paper, a method for realizing a shape-maintained tree deformation animation based on a sketch was proposed, which comprises the steps that a 3D tree model is created; the three-dimensional tree model was expressed with a framework and leaf clusters; a view-of-interest is selected, a crown silhouette line of the three dimensional tree model in the step (2) is detected, and adeformation animation target crown silhouettes line is drawn on the sketch; the crown silhouette lines of the 3D model was gradually deformed to become the deformation
Abstract: The invention discloses a method for realizing a shape-maintained tree deformation animation based on a sketch. The method comprises the steps that a three-dimensional tree model is created; the three-dimensional tree model is expressed with a framework and leaf clusters; a view-of-interest is selected, a crown silhouette line of the three-dimensional tree model in the step (2) is detected, and adeformation animation target crown silhouette line is drawn on the sketch; the crown silhouette line of the three-dimensional tree model is gradually deformed to become the deformation animation target crown silhouette line, and deformation of the crown silhouette line of the three-dimensional tree model is transmitted to branches to obtain a smooth tree deformation process; and the deformation process of the crown silhouette line and the branches is recorded frame by frame to obtain the shape-maintained tree deformation animation. Through the method, tree topological consistency and crown morphological significance are maintained, visual three-dimensional tree editing operation is also provided, and the three-dimensional tree model can be effectively edited just by drawing the simple sketch.
2 citations
Journal Article•
TL;DR: The internet community has recently been focused on peer-to-peer systems, and so happened to distributed database which uses functional dependency to reduce the operation on the node in P2P system.
Abstract: The internet community has recently been focused on peer-to-peer systems, and so happened to distributed database. The tree model is divided which is popular used into actomic model. The model uses functional dependency to reduce the operation on the node in P2P system.
2 citations