Recognition tunneling (RT) is an emerging technique for investigating single molecules in a tunnel junction. We have previously demonstrated its capability of single molecule detection and identification, as well as probing the dynamics of intermolecular bonding at the single molecule level. Here by introducing cucurbituril as a new class of recognition molecule, we demonstrate a powerful platform for electronically investigating the host-guest chemistry at single molecule level. In this report, we first investigated the single molecule electrical properties of cucurbituril in a tunnel junction. Then we studied two model guest molecules, aminoferrocene and amantadine, which were encapsulated by cucurbituril. Small differences in conductance and lifetime can be recognized between the host-guest complexes with the inclusion of different guest molecules. By using a machine learning algorithm to classify the RT signals in a hyper dimensional space, the accuracy of guest molecule recognition can be significantly improved, suggesting the possibility of using cucurbituril molecule for single molecule identification. This work enables a new class of recognition molecule for RT technique and opens the door for detecting a vast variety of small molecules by electrical measurements.