In machine learning, models train on a large amount of data, but tests should be tested before use in real life. If the test data is very similar to training, the model may show good results, but it may fail in real tasks. DataSail helps to avoid it and makes the test more honest.
Ordinary algorithms do not know how the data is qualitatively separated, so many AI systems are actually overly valued. The new vehicle automatically creates two different data sets by eliminating this problem.
DataSail works with all kinds of data. It is enough for the user to specify a few parameters, the rest of the program does this yourself. This is also the first tool that can work with these interactions – for example, for tasks in drugs where it is important to understand how the drug interacts with different proteins.
Source: Ferra
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