Machine learning based methane emissions monitoring

A system comprising:

• at least one processor;
• and
• an application that, when executing on the at least one processor, performs:
• collecting sensor data from a plurality of sensors;
• applying an augmentation model to the sensor data to form a regression training set;
• creating a classification training set for a classification model by replacing regression output values from the regression training set with classification output values, wherein the classification output values comprise binary values;
• training the regression model with the regression training set to generate a regression prediction;
• and
• training the classification model with the classification training set to generate a classification prediction.

A non-transitory computer readable medium comprising instructions that, when executed by one or more processors, perform:

• collecting sensor data from a plurality of sensors;
• applying an augmentation model to the sensor data to form a regression training set;
• creating a classification training set for a classification model by replacing regression output values from the regression training set with classification output values, wherein the classification output values comprise binary values;
• training the regression model with the regression training set to generate a regression prediction;
• and
• training the classification model with the classification training set to generate a classification prediction.