Gretel's New Synthetic Performance Report

Gretel's Premium SDK now includes detailed reporting that shows the accuracy of synthetic data's statistical distributions and correlations. The performance report provides interactive Plotly graphs and stylish HTML formatting, allowing users to assess how well their training data's distributions were maintained in the new synthetic data. Key metrics include duplicated lines between training and synthetic data, Mean Squared Error (MAE) for field correlations, and Jensen-Shannon Distance for within-field distribution maintenance. The report also includes a breakdown of JS Distance scores for each individual field, as well as a heatmap showing the differences in correlation values between the original and synthetic datasets. Users can improve their model's performance by retraining it multiple times, increasing the number of training examples or epochs, adjusting rnn_units parameter, or experimenting with dropout_rate.

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