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In this section, the experimental evaluation of the framework devoted to soft biometric estimations is reported.
Results reported in this paper focus only on presenting the development phases and evaluation of the framework.
The evaluation of the framework was also discussed based on the implementation details provided in this paper.
We also present a thorough evaluation of the framework with different patch generation methods, forest training mechanisms and prediction methods.
In their research, new features were iteratively constructed using decision trees, while the evaluation of the framework was done using the Irvine repository of (symbolic) classification problems.
Experimental evaluation of the framework demonstrates that the proposed approach compares favorably with the previous technique in a set of shape retrieval experiments for different datasets.
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Future research should involve evaluations of the framework in other health service settings where comprehensive HISs are developed.
The focus of this paper is on the experimental evaluation of this framework.
The next section reconstructs the development and evaluation phases of the framework and briefly explains the context surrounding each update of MLFAF.
An extensive evaluation of the proposed framework.
Table 1 Parameters for evaluation of the proposed framework.
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evaluation of the environment
rate of the framework
evaluation of the law
tests of the framework
evaluation of the environments
evaluation of the plans
evaluations of the framework
evaluation of the policies
evaluation of the frames
evaluation of the programme
evaluation of the state
evaluation of the risk
evaluation of the selection
evaluation of the protocol
evaluation of the situation
evaluation of the trial
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