Method and an apparatus for functional model generation
The present disclosure is generally related to an apparatus and a method receiving system data, classifying the system data to a concern category, and generating, at least a tailored recommendation as a function of the classified system data. Further, the method may include generating a functional model as a function of the at least a tailored recommendation, transmitting the at least a tailored recommendation and the function model to a display, and displaying the at least a tailored recommendation and the functional model as a geometrical depiction.
1 . An apparatus for functional model generation, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the at least processor, the memory containing instructions configuring the at least processor to:
receive enterprise data regarding an enterprise having a plurality of entities, wherein:
the enterprise data comprises image data; and
receiving the enterprise data further comprises collecting the enterprise data using a web crawler;
classify the enterprise data to a concern category, wherein classifying the enterprise data comprises classifying the image data to a concern category as a function of an image classifier;
generate, using a recommendation machine learning model, at least a tailored recommendation as a function of the classified enterprise data, wherein generating at least a tailored recommendation comprises training a recommendation machine learning model using training data, wherein the training data comprises previous iterations of the recommendation machine learning model, wherein the previous iterations comprise classified enterprise data inputs and correlated tailored recommendation outputs;
generate a functional model as a function of the at least a tailored recommendation;
transmit the at least a tailored recommendation and the function model to a display;
display the at least a tailored recommendation and the functional model as a geometrical depiction, wherein:
the geometrical depiction includes a plurality of depictions, wherein each icon of the plurality of depictions depicts an entity of the plurality of entities; and
displaying the geometrical depiction includes identifying that an entity of the plurality of entities is an outlier entity and highlighting a depiction of the plurality of depictions that is associated with the outlier entity; and
select the at least a tailored recommendation, wherein a connectivity line between the plurality of entities is modified based on the selection.
2 . The apparatus of claim 1 , wherein receiving the enterprise data comprises receiving image data.
3 . The apparatus of claim 2 , wherein the image data comprises processed image data, and wherein processing the image data comprises upsampling the image data to a desired pixel count.
4 . The apparatus of claim 1 , wherein classifying the enterprise data further comprises utilizing a classifier machine-learning model.
5 . The apparatus of claim 4 , wherein utilizing the classifier machine-learning model comprises training the machine-learning model.
6 . The apparatus of claim 1 , wherein generating the at least a tailored recommendation comprises identifying a pattern of activity in enterprise data.
7 . The apparatus of claim 6 , wherein identifying the pattern of activity in enterprise data further comprises identifying an occurrence frequency of the pattern of activity.
8 . The apparatus of claim 1 , wherein generating a functional model comprises ranking the at least a tailored recommendation.
9 . The apparatus of claim 8 , wherein generating the function model further comprises utilizing a function model machine-learning model.
10 . The apparatus of claim 1 , wherein transmitting the at least a tailored recommendation and the functional model comprises satisfying a percent loss threshold.
11 . A method for determining tailored recommendations for an enterprise, the method comprising:
receiving, by a processor, enterprise data regarding an enterprise having a plurality of entities, wherein:
the enterprise data comprises image data; and
receiving the enterprise data further comprises collecting the enterprise data using a webcrawler;
classifying, by the processor, the enterprise data to a concern category, wherein classifying the enterprise data comprises classifying the image data to a concern category as a function of an image classifier;
generating, by the processor, at least a tailored recommendation as a function of the classified enterprise data, wherein generating at least a tailored recommendation comprises training a recommendation machine learning model using training data, wherein the training data comprises previous iterations of the recommendation machine learning model, wherein the previous iterations comprise classified enterprise data inputs and correlated tailored recommendation outputs;
generating, by the processor, a functional model as a function of the at least a tailored recommendation;
transmitting, by the processor, the at least a tailored recommendation and the function model to a display;
displaying, by a display, the at least a tailored recommendation and the functional model as a geometrical depiction, wherein:
the geometrical depiction includes a plurality of depictions, wherein each icon of the plurality of depictions depicts an entity of the plurality of entities; and
displaying the geometrical depiction includes identifying that an entity of the plurality of entities is an outlier entity and highlighting a depiction of the plurality of depictions that is associated with the outlier entity; and
selecting the at least a tailored recommendation, wherein a connectivity line between the plurality of entities is modified based on the selection.
12 . The method of claim 11 , wherein receiving the enterprise data comprises receiving image data.
13 . The method of claim 12 , wherein receiving the image data comprises receiving processed image data, and wherein processing the image data comprises upsampling the image data to a desired pixel count.
14 . The method of claim 11 , wherein classifying the enterprise data further comprises utilizing a classifier machine-learning model.
15 . The method of claim 14 , wherein utilizing the classifier machine-learning model comprises training the machine-learning model.
16 . The method of claim 11 , wherein generating the at least a tailored recommendation comprises identifying a pattern of activity in enterprise data.
17 . The method of claim 16 , wherein identifying the pattern of activity in enterprise data further comprises identifying an occurrence frequency of the pattern of activity.
18 . The method of claim 11 , wherein generating a functional model comprises ranking the at least a tailored recommendation.
19 . The method of claim 18 , wherein generating the function model further comprises utilizing a function model machine-learning model.
20 . The method of claim 11 , wherein transmitting the at least a tailored recommendation and the functional model comprises satisfying a percent loss threshold.