The invention discloses a data evaluation method and device,
terminal equipment and a storage medium. The method comprises the following steps of carrying out preprocessing on sample variables in a sample
data set in order to obtain nominal variables which are ordered according to the sizes of characteristic values; carrying out one-hot coding on the nominal variables which are ordered according to the sizes of the characteristic values, and converting the nominal variables into digital variables; applying a gradient lifting decision-making tree
algorithm to the sample
data set containing thedigital variables; generating a
decision tree model comprising n decision trees; and acquiring combined characteristics by adopting the gradient lifting decision-making tree
algorithm. The accuracy ofprediction of the combined characteristics of sample data is improved, and the efficiency of acquisition of the combined characteristics is also improved, so that the combined characteristics are used as input characteristics of a
binary logic regression model to carry out prediction of a preset event result, and thus the complexity and the uncertainty of manual searching of the characteristics are avoided, the prediction accuracy of the sample data for the preset event result is improved, and meanwhile, the accuracy and the efficiency of sample data evaluation are also improved.