This method is based on the combination of results from different prediction models. In article two
The proposed model is presented in a model of model training using the data set containing
The subset of attributes is used with two data models of genetic algorithm and forest and in model
The second suggestion is the combination of training the neural network with the meta-algorithms and the first proposed model for production
We have used educational data sets. In fact, there are two separate processes in this model. One
The process for producing different training collections and the other task of training the neural network using
Hyper-market algorithms. In the models, the genetic algorithm and algorithm are used as two algorithms
We have used famous metropolitan areas to produce educational collections. Parameters affecting on
Classification of data in both models and model evaluation criteria TPR sensitivity TNR transparency and
The accuracy and accuracy of the tests are due to the large amount of data in the three important criteria
, Accuracy has been paid.
Dir Sir,
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