Whenever we are feeding the data to the ML model, the quality of data and how related the features are with the outcome usually determines the quality of the predictive model. If there are features that are not highly correlated with the outcome, there is a minimal chance of success with using the models from the simplest of models to the most complex models. Therefore, the most important aspect that must be considered as a data scientist or a machine learning engineer is the quality of data being given to various models.

I hope this gives you some insight.
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