Recommend Modules for My Data

You can use Recommend Modules for My Data module to find the right modules to clean and transform your dataset. For example, let's take a look at an example of a messy dataset. You can find the sample experiment with this dataset [here][1]. ![Screenshot of messy data][2] All columns in this dataset, except first two, have some data quality issue: missing values, NaN or Inf values, too many unique values, free-form text fields that have to pre-processed, and few strings mixed in with numeric data. To get module recommendations to fix these issues, we simply pass this data to the module: ![enter image description here][3] By clicking the output port of the module we can view the list of module recommendations, which columns should be transformed, and more detailed description of the issue and recommended action. ![enter image description here][4] The module checks the columns in the dataset for following issues: - Some missing values (<=50%) - Lots of missing value (>50%) - NaN values - Inf values - Large proportion of non-numeric unique values that may led to overfitting - Whitespace-tokenized text content - Constant data that has no predictive value - Few string values mixed in with otherwise numeric data The R source code of the module is available at GitHub [here][5]. [1]: http://gallery.cortanaintelligence.com/Experiment/Recommend-Modules-for-My-Data-1 [2]: https://ctpsamples.blob.core.windows.net/customoduleimages/recommendmodules1.PNG [3]: https://ctpsamples.blob.core.windows.net/customoduleimages/recommendmodules2.PNG [4]: https://ctpsamples.blob.core.windows.net/customoduleimages/recommendmodules3.PNG [5]: https://github.com/Azure/custmod/tree/master/RecommendModulesForMyData