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TRANSFORMING ATTRIBUTES FOR TRAINING AUTOMATED MODELING SYSTEMS

  • US 20190205791A1
  • Filed: 09/21/2017
  • Published: 07/04/2019
  • Est. Priority Date: 09/21/2016
  • Status: Active Grant
First Claim
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1. A system comprising:

  • a processing device; and

    one or more memory devices storing;

    instructions executable by the processing device,a machine-learning model that is a memory structure comprising input nodes interconnected with one or more output nodes via intermediate nodes, wherein the intermediate nodes are configured to transform input attribute values into a predictive or analytical output value for an entity associated with the input attribute values, andtraining data for training the machine-learning model, wherein the training data is grouped into attributes;

    wherein the processing device is configured to access the one or more memory devices and thereby execute the instructions to;

    select a subset of attributes from the attributes of the training data;

    transform the subset of attributes into a transformed attribute by performing operations comprising;

    grouping portions of the training data for the subset of attributes into respective multi-dimensional bins, wherein each dimension for the multi-dimension bins corresponds to a respective one of the attributes in the subset of attributes,computing interim predictive output values, wherein each interim predictive output value is generated from a respective training data portion in a respective one of the multi-dimensional bins,computing smoothed interim output values by applying a smoothing function to the interim predictive output values, andoutputting the smoothed interim output values as a dataset for the transformed attribute; and

    train the machine-learning model with the transformed attribute.

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