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Moreover, we found some interesting explanation about the property of CMM based on chemical information by using the selected descriptors.
Linear and nonlinear models were developed using the selected descriptors.
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The selected descriptors using two approaches were basically the same type of molecular descriptors.
In the next stage, the selected descriptors were used to derive non-linear models using SVR and ANN.
The selected descriptors are then used for developing the QSAR prediction models by using the MLR, DT and ANN approaches.
The selected descriptors were used as inputs for SVM model.
The selected descriptors were used as input neurons in a wavelet neural network (WNN) model.
The selected descriptors were used as input nodes in a wavelet neural network (WNN) model.
The selected descriptors are used as the input attributes to the system of classifiers, responsible for the final recognition of melanoma.
The selected descriptors were used to develop six MLR equations containing 1 6 descriptors.
The selected descriptors were then used to perform an MLR study until a valid model including: the critical probability P value < 0.05 for all descriptors and for the complete model, The Fisher static, the coefficient of determination, the mean squared error and the multi-collinearity test, internal and external validations, in addition to the Y-Randomization.
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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