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On the other hand, our method is more robust against the changing values of features.
Additionally, values of features in this dataset are ordinal data type.
First one is to compute cluster prototypes, v i for each cluster i. Cluster prototypes refer to the average values of features of member objects (real data, z k ), weighted by membership degree of the object.
The procedure adopted by authors in developing predictive model is first preprocessed the dataset, then compute F-score values of features, select features with high F-score as discriminative features, then k-means algorithm is used to select feature subset that gives minimum clustering error and finally SVM is used to classification [27] as shown in Fig. 4.
RP-ROC requires complete data, where no values of features are missing, whereas CART does not.
For example, correlation values of features at p1 and p1′ are computed, and then features are sorted based on them.
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Note that |S| is the number of possible values feature x can take, while | S i | is the number of actual values of feature x.
where FAWGN and FBi-kappa are the values of feature under consideration computed in the presence of AWGN and bi-kappa noise, respectively, at a particular SNR.
For example, the values of Feature 1 range from 1 to 6842; and those of Feature 2 values range from 3 to 11,571 across the bots in CTU-13 datasets.
Adaptive feature scaling factors were introduced as an inherent mechanism that enables RVMs to identify the relative importance of each input factor, and an optimization method for obtaining the appropriate values of feature scaling factors is proposed.
There is iterative calculation until the two values of feature vector difference are less than the set value of ε.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com