SVM approach for predicting LogP
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The logarithm of the partition coefficient between n-octanol and water (logP) is an important parameter for drug discovery. Based upon the comparison of several prediction logP models, i.e. Support Vector Machines (SVM), Partial Least Squares (PLS) and Multiple Linear Regression (MLR), the authors reported SVM model is the best one in this paper.
Key wordsLogP prediction multiple linear regression (MLR) partial least squares (PLS) support vector machines (SVM)
the logarithm of the partition coefficient between n-octanol and water
support vector machines
partial least squares
multiple linear regression
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