The first thing to do is to create a model builder from a Watson Studio project.
Import input CSV data in the experiment UI. how to map CSV input and output data to OPL models in WS/WML,.how CSV are normally used in experiment UI,.dat, while in the model builder, data should be provided as. Choosing between OPL and docplex might be a thought decision.Īlong with OPL model, legacy environments allowed to provide data using another dedicated syntax known as. So it has been made possible to also use OPL in the model builder. Still, many Operation Research practitioners prefer to use a dedicated language for optimization modeling, such as OPL (Optimization Programming). This can be done both using notebooks or the dedicated model builder (now called Decision Optimization experiment). The recommended modeling language is Python using the docplex package. This post provides some hints about it.Īs part of the integration of Decision Optimization into Watson Studio, focus has been put on homogenizing around data science practices. Taking full advantage of Decision Optimization in Watson Studio and Watson Machine Learning with OPL requires the use of CSV input files.
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