Best machine learning model for binary variables input and categorical output?

I have a training dataset which has 18 binary variables (predictors) with values 1/0. The response is categorical (High/Low). Right now I am the classification learner app but the accuracy is only 56%. Can anyone please suggest me some better approaches to improve the model accuracy? I used 10000 data. Maybe my training dataset is too small?