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AutoML performs automatic sensor selection, feature selection, and hyper-parameter optimization to maximize the performance of small datasets. However, if the data does not sufficiently represent the statistical diversity needed for building good machine learning models, more data is recommended. You can see if more data will help with accuracy through the learning curves generated for each model.