f8175e0221bbf31ffc8c10ee809b7ee2e118362d,oddt/scoring/functions/RFScore.py,rfscore,train,#rfscore#Any#Any#Any#,93

Before Change

        error = rmse(self.model.predict(self.test_descs), self.test_target)
        r2 = self.model.score(self.test_descs, self.test_target)
        r = np.sqrt(r2)
        print("Test set:",
              "R**2: %.4f" % r2,
              "R: %.4f" % r,
              "RMSE: %.4f" % error,
              sep="\t", file=sys.stderr)

        error = rmse(self.model.predict(self.train_descs), self.train_target)
        oob_error = rmse(self.model.oob_prediction_, self.train_target)
        r2 = self.model.score(self.train_descs, self.train_target)

After Change

        print("Training RFScore v%i on PDBBind v%i"
              % (self.version, pdbbind_version), file=sys.stderr)

        sets = [
            ("Test", self.model.predict(self.test_descs), self.test_target),
            ("Train", self.model.predict(self.train_descs), self.train_target),
            ("OOB", self.model.oob_prediction_, self.train_target)]

        for name, pred, target in sets:
            print("%s set:" % name,
                  "R2_score: %.4f" % r2_score(target, pred),
                  "Rp: %.4f" % pearsonr(target, pred)[0],
                  "RMSE: %.4f" % rmse(target, pred),
                  sep="\t", file=sys.stderr)

        // compile trees
        if compiledtrees is not None:
            try:
                print("Compiling Random Forest using sklearn-compiledtrees",
                      file=sys.stderr)

Instances