Dimensional isolation prediction in video delivery systems

A method comprising:

• separating, by a computing device, a plurality of subscriber features generated from a subscriber's interactions with a video delivery service into a plurality of feature dimensions;
• inputting, by the computing device, each of the plurality of feature dimensions into a respective prediction network of a plurality of prediction networks, wherein each prediction network in the plurality of prediction networks is trained to output a respective dimension score;
• outputting, by the computing device, a plurality of dimension scores from the plurality of prediction networks using parameters in the plurality of prediction networks that are trained using a variance term to control a variance of the plurality of feature dimensions and using a de-correlation term to control a correlation of the plurality of feature dimensions, wherein the de-correlation term adds a sum over off-diagonal elements of a correlation matrix to a cost function that is minimized;
• combining, by the computing device, the plurality of dimension scores into a retention prediction score;
• and
• performing, by the computing device, an action on the video delivery service for the subscriber based on the retention score.

A method comprising:

• separating, by a computing device, a plurality of subscriber features generated from a subscriber's interactions with a video delivery service into a plurality of feature dimensions;
• inputting, by the computing device, each of the plurality of feature dimensions into a respective prediction network of a plurality of prediction networks, wherein each prediction network in the plurality of prediction networks is trained to output a respective dimension score;
• outputting, by the computing device, a plurality of dimension scores from the plurality of prediction networks using parameters in the plurality of prediction networks that are trained using a variance term to control a variance of the plurality of feature dimensions and using a de-correlation term to control a correlation of the plurality of feature dimensions;
• combining, by the computing device, the plurality of dimension scores into a retention prediction score, wherein combining the plurality of dimension scores into the retention prediction score comprises multiplying the plurality of dimension scores to generate the retention prediction score;
• and
• performing, by the computing device, an action on the video delivery service for the subscriber based on the retention score.

A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for:

• separating a plurality of subscriber features generated from a subscriber's interactions with a video delivery service into a plurality of feature dimensions;
• inputting each of the plurality of feature dimensions into a respective prediction network of a plurality of prediction networks, wherein each prediction network in the plurality of prediction networks is trained to output a respective dimension score;
• outputting a plurality of dimension scores from the plurality of prediction networks using parameters in the plurality of prediction networks that are trained using a variance term to control a variance of the plurality of feature dimensions and using a decorrelation term to control a correlation of the plurality of feature dimensions, wherein:
• a first de-correlation term is used for all active subscribers, and
• a second de-correlation term is used for a portion of the plurality of dimensions;
• combining the plurality of dimension scores into a retention prediction score;
• and
• performing an action on the video delivery service for the subscriber based on the retention score.

A method comprising:

• outputting, by a computing device, a plurality of dimension scores from a plurality of prediction networks using a plurality of subscriber features generated from a subscriber's interactions with a video delivery service for a subscriber, wherein outputting the plurality of dimension scores comprises disabling a portion of the plurality of dimension scores during the training of the prediction networks of inactive subscribers;
• combining, by the computing device, the plurality of scores into a retention prediction score;
• evaluating, by the computing device, the retention prediction score and a result of whether the subscriber cancelled the video delivery service, wherein the evaluating uses a variance term to control a variance of the plurality of feature dimensions and a de-correlation term to control a correlation of the plurality of feature dimensions;
• and
• adjusting, by the computing device, a set of parameters for one or more of the plurality of prediction networks based on the evaluating.