chemoinformatics toolkit

# Solubility Predicts log S. Log S greater than -4 is soluble. Root mean square error of 1.27 on a scale from -4 to 4. linear regression

Build a SAR model cross entropy- default loss function for binary classification problems. Summarizes the average difference between the actual and predicted probability. hinge- alternative to cross entropy binary classification developed with SVM models used with support vector machine models mse-default loss to use for regression problems. calculated as the average of the squared differences between the predicted and actual values mae-for regression problems. used in cases where there are outliers. average of the absolute difference between actual and predicted values

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