How to publish a simple machine-learning approach that cannot compete with the state of the art?
If you try to avoid the benchmark metrics comparison, it is going to be the 900 pound gorilla in the back of the mind of everyone reading your paper.

The alternative is to deal with it from the start. You obviously think there are reasons why your technique is interesting despite its benchmark metrics. You need to communicate those reasons. They should be first mentioned in the abstract. That way, readers are more likely to suspend thinking about the benchmark metrics issue in favor of thinking about what makes the technique interesting.

At some point in the paper you will need to present some metrics, in order to support a claim that the simplicity of your technique outweighs the metrics for some situations.