Ensemble feature selection through rank aggregation method can be carried out using aggregation operators. In this article, the Bonferroni Logarithmic induced ordered weighted averaging operator is proposed to handle the dimensionality reduction issue. This operator combines the advantages of Bonferroni mean operator, Logarithmic function and induced weighted ordered averaging operator. The proposed technique is evaluated on high-dimensional datasets to show its efficacy while comparing it with the existing techniques. Statistical significance tests are also carried out to show the significance of the proposed technique.