Making new drugs or attaining new validated research results takes a long time and consumes human resources and financial resources. TADA can help researchers find new purposes for their discoveries and extend the reach of their research.
You have identified a pattern, a conjunction of factors that indicate a threat. Use TADA to model it into an equation. Share the equation, and have anybody, anywhere, access local data identify this threat, too, thanks to your work.
Train your model on few historical data (one hundred records is enough) and apply it to new similar research to speed up the research cycle.
Data is generated by experimental research. Often, a researcher generates between a few hundred and thousands of records of data. TADA is efficient with as low as one hundred records.
Sensitivity Analysis provides researchers with the critical criteria impacting the results according to TADA. It is a powerful feature that shifts the power of the analysis from the TADA to the researcher.
It isn’t straightforward to understand the accuracy of a Machine Learning model without being a Data Scientist. The global score is a global measure of a model’s accuracy computed by TADA. It enables the comparison between different models.
The Live Predict feature allows researchers to vary one of the critical parameters and values that are not present in the dataset. The purpose is to measure the impact of such a parameter on the prediction.
Live Predict allows to tweak and explore a model generated by TADA. Once an interesting configuration is found, TADA allows saving this simulation for future use.