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The performance of predictive modeling is dependent on the amount and quality of available data.

Domain expert machine learning. Done right machine learning does not replace the expertise of the professionals that use contract analysis software. The problem isn t an either or issue but rather requires both parties to come to the table. This poll was motivated by a panel at a recent strata 2012 conference which debated the question in data science domain expertise is more important than machine learning skill.

An expert specifies all. The software amplifies that expertise by embedding the professionals knowledge in analytical tools and applying. The audience at that debate split almost evenly on this question.

Machine learning and expert systems differ in the quantity of human knowledge needed and how they are used. The method exploits advantages in domain knowledge and machine learning as complementary information sources. Whereas machine learning may discover patterns in interest domains that are too subtle for humans to detect domain knowledge may contain information on a domain not present in the available domain dataset.

In an expert system the full knowledge of the expert acquired is digitized and is used in the decision making. Oag analytics combines domain expert algorithms and machine learning for optimum well spacing through the combination of data visualization software and a cloud ml solution it successfully improved predictability of tightly spaced wells creating a huge value add for oil and gas companies. Data scientists with strong machine learning skills and an analytical mind can quickly grasp and solve business problems by exchanging and sharing their acquired domain learning with domain experts at different stages of system development.

This leads to non recoverable losses through incorrect decision making and mismatches between plant operating settings and the characteristics of the. How do you know that these features are important. Can machine learning on big data replace domain expertise.

A good example is feature extraction. Salary may be good features in knowing ab. In 2008 he was named to the mit technology review tr35 as one of the top 35 innovators in the world under the age of 35.

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