| CPC G06N 7/01 (2023.01) [G06F 9/451 (2018.02); G06Q 10/06375 (2013.01); G06Q 40/00 (2013.01)] | 20 Claims |
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1. An apparatus for determining the resilience of an entity, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:
receive entity data from a user wherein the entity data comprises image data pre-processed using an optical character reader to convert the image data into machine-encoded text;
select at least one probability indicator as a function of the entity data, wherein the at least one probability indicator receives indicator training data having a plurality of entity data correlated to a plurality of the probability indicators;
determine a life probability of the entity as a function of the at least one probability indicator comprising;
iteratively training a life machine learning model, as a function of the life training data, wherein iteratively training the life machine learning model further comprises:
using life training data applied to an input layer of nodes comprising at least one probability indicator input, one or more intermediate layers of nodes, and an output layer of nodes comprising a plurality of life probability outputs;
adjusting one or more connections and one or more weights between nodes in adjacent layers of the recommendation machine learning model;
comparing the output layer of nodes and the input layer of nodes to generate an error function;
updating the one or more weights iteratively based on the error function to enhance a degree of accuracy of the one or more weights; and
retraining the recommendation machine learning model as a function of the updated one or more weights; and
determining the life probability as a function of the life machine learning model; and
generate a growth approach as a function of the life probability.
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