The variable connectivity index (1)chi(f) versus the traditional moleculardescriptors: A comparative study of (1)chi(f) against descriptors of CODESSA

In this study we compared the prediction abilities of the variable connecti vity index (1)chi (f) (not included in CODESSA) with topological indices av ailable from CODESSA. We selected the boiling points of n = 100 alcohols as the property and examined the pool of 56 topological indices. Prediction c apabilities of the developed models were evaluated by clasical training/tes t set approach. RMS errors calculated from the prediction set for the MLR m odels obtained from CODESSA software with 1, 2, 3, 4, and 5 parameters were 9.06, 5.69, 5.40, 4.9, and 3.37 degreesC, respectively. Using the variable connectivity index with weights x = 0.10 and y = -0.92 for carbon and oxyg en atom respectively, we obtain regression BP = 38.12 (1)chi (f) - 37.56 wi th the correlation coefficient r = 0.9915, RMS error 4.21 degreesC calculat ed from the test set, and Fisher ratio F = 5691. Prediction capability of t he variable connectivity index was better than for MLR regression model wit h up to four parameters.