Cross-validation

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    Categories: Data Science

    The process of dividing available data into a test set and a training set. Training is then done on the training set, and then to test the performance of the learned model it is applied to the test set (or ‘control set’). Cross-vaildation, therefore, helps us to evaluate the performance of a model to make predictions on unseen data.

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    Justin Chan
    Dr Chan founded DataDrivenInvestor.com (DDI) and is the CEO for JCube Capital Partners. Specialized in strategy development, alternative data analytics and behavioral finance, Dr Chan also has extensive experience in investment management and financial services industries. Prior to forming JCube and DDI, Dr Chan served in the capacity of strategy development in multiple hedge funds, fintech companies, and also served as a senior quantitative strategist at GMO. A published author at professional journals in finance, Dr. Chan holds a Ph.D. degree in finance from UCLA.