Model Validation and Testing: A Step-by-Step Guide | Built In
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Model validation is a phase in the machine learning process where a trained model’s performance is evaluated using a validation data set, which contains new, unseen that is different from training data.
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For Analytic Solver, partition the data sets into 50% training, 30% validation, and 20% test and use 12345 as the default random seed.When searching for the optimal value of k, search within possible k values from 1 to 10. If the predictor variable values are in thecharacter format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numericalvariable.The Chartered Financial Analyst (CFA) designation is the de facto professional certification
For Analytic Solver, partition the data sets into 50% training, 30% validation, and 20% test and use 12345 as the default random seed.When searching for the optimal value of k, search within possible k values from 1 to 10. If the predictor variable values are in thecharacter format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numericalvariable.The Chartered Financial Analyst (CFA) designation is the de facto professional certification
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Weka Tutorial 35: Creating Training; Validation and Test Sets (Data Preprocessing) Video Lecture | Weka Tutorial - Data and Analytics
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