Experiment 2: the comparison between the weighted CBR and unweighted CBR Since there is no weighting operation in traditional CBR, each feature is assigned a weight of 1. Assigning different weights to the features of each case was expected to improve the recommendation accuracy.
where and denotes the (multiplicative) weighting operation.
Thus, the weighting operation was necessary for CBR.
A filtering framework cannot be considered complete until an appropriate weighting operation is defined.
This illustrated not only that the weighting operation was necessary for case matching, but also that the proposed approach was superior to the unweighted CBR approach.
Moreover, a pilot software tool has been developed to support the needs related to real time, cloud-based, light weight operation.
Since there is no weighting operation in traditional CBR, each feature is assigned a weight of 1. Assigning different weights to the features of each case was expected to improve the recommendation accuracy.
And a compact synaptic circuit based on memristors is designed to realize the cloning template parameter (weight strength) and the multiplication (weighting) operation, by leveraging its nonvolatility, good scalability, and variable conductance.
After the final iteration of the iterative detection process, the estimates of the messages of the correct relays and the estimates of the messages of the erroneous relays are combined using a weighting operation similar to [16] in order to estimate the source messages.
2) Did the proposed weighting operation improve the diagnostic performance of the system? 3) Did the CBR CDSS more aptly diagnosis PM and PTTH compared to the guideline-based CDSS? 1. Experiment 1: the variation in performance as the value of K varies In the KNN method, the value of K is most influential to the recommendation performance.
No significant difference was found between the groups of patients in age, weight, operation time or history (P > 0.05).
