System and method for text-based conversation with a user, using machine learning

1. A method of text-based conversation with a user, using machine learning, the method comprising:

receiving, using a computing device, at least a feature associated with a user's condition and at least a preference input;

generating, using the computing device, a probabilistic output, wherein generating the probabilistic output further comprises:

inputting the at least a feature to a probabilistic machine learning model; and,

generating the probabilistic output as a function of the probabilistic machine learning model;

classifying, using the computing device, the probabilistic output and the at least a feature to an intervention class, wherein classifying further comprises:

inputting the probabilistic output and the at least a feature to a classifying machine learning model; and

classifying the probabilistic output and the at least a feature to the intervention class as a function of the classifying machine learning model;

interfacing conversationally, using the computing device, with the user, wherein interfacing conversationally further comprises:

generating text as a function of the intervention class and the at least a preference input; and

interfacing conversationally using the generated text;

waiting, using the computing device, for a timeframe to elapse;

receiving, using the computing device, at least a second feature associated with the user's condition and at least a second preference input;

generating, using the computing device, a second probabilistic output, wherein generating the second probabilistic output further comprises:

inputting the at least a second feature to the probabilistic machine learning model; and

generating the second probabilistic output as a function of the probabilistic machine learning model; and

classifying, using the computing device, a second intervention class, wherein classifying the second intervention class further comprises:

inputting the second probabilistic output and the at least a second feature to the classifying machine learning model; and

classifying the second probabilistic output and the at least a second feature to the second intervention class as a function of the classifying machine learning model.

2. The method of claim 1 , further comprising:

training, using the computing device, the probabilistic machine learning model, wherein training the probabilistic machine learning model further comprises:

inputting training data to a machine learning algorithm, wherein the training data comprises a plurality of features correlated to a probabilistic outcome; and

training the probabilistic machine learning model as a function of the machine learning algorithm.

3. The method of claim 1 , further comprising:

training, using the computing device, the classifying machine learning model, wherein training the classifying machine learning model further comprises:

inputting training data to a machine learning algorithm, wherein the training data comprises a plurality of features; and

training the probabilistic machine learning model as a function of the machine learning algorithm.

4. The method of claim 1 , wherein interfacing conversationally further comprises:

receiving, using the computing device, a submission;

recognizing, using the computing device, at least a word from the submission, wherein recognizing the at least a word further comprises:

inputting the submission to a language processing model; and

recognizing the at least a word as a function of the language processing model; and

generating, using the computing device, a response as a function of the at least a word.

5. The method of claim 4 , further comprising:

training, using the computing device, the language processing model, wherein training the language processing model further comprises:

inputting training data to a natural language processing algorithm; and

training the language processing model as a function of the natural language processing algorithm and the training data.

6. The method of claim 1 , further comprising:

generating, using the computing device, at least a metric, wherein generating the at least a metric further comprises:

inputting the intervention class to a machine learning model; and

generating the at least a metric as a function of the machine learning model.

7. The method of claim 6 , wherein interfacing conversationally further comprises:

receiving, using the computing device, a submission from the user;

recognizing, using the computing device, at least a datum from the submission, wherein recognizing the at least a datum further comprises:

inputting the submission to a language processing model; and

recognizing the at least a datum as a function of the language processing model;

wherein the at least a datum is associated with the at least a metric.

8. The method of claim 1 , further comprising selecting the classifying machine learning model from a plurality of classifying machine learning models as a function of the at least a feature.

9. The method of claim 1 , further comprising selecting training data as a function of the at least a feature; and

training the classifying machine-learning model using the training data.

10. A system for text-based conversation with a user, using machine learning, the system comprising a computing device configured to:

receive at least a feature associated with a user's condition and at least a preference input;

generate a probabilistic output, wherein generating the probabilistic output further comprises:

inputting the at least a feature to a probabilistic machine learning model; and,

generating the probabilistic output as a function of the probabilistic machine learning model;

classify the probabilistic output and the at least a feature to an intervention class, wherein classifying further comprises:

inputting the probabilistic output and the at least a feature to a classifying machine learning model; and

classifying the probabilistic output and the at least a feature to the intervention class as a function of the classifying machine learning model;

interface conversationally with the user, wherein interfacing conversationally further comprises:

generating text as a function of the intervention class and the at least a preference input; and

interfacing conversationally using the generated text;

wait for a timeframe to elapse;

receive at least a second feature associated with the user's condition and at least a second preference input;

generate a second probabilistic output, wherein generating the second probabilistic output further comprises:

inputting the at least a second feature to the probabilistic machine learning model; and

generating the second probabilistic output as a function of the probabilistic machine learning model; and

classify a second intervention class, wherein classifying the second intervention class further comprises:

inputting the second probabilistic output and the at least a second preference input to the classifying machine learning model; and

classifying the second probabilistic output and the at least a second preference input to the second intervention class as a function of the classifying machine learning model.

11. The system of claim 10 , wherein the computing device is further configured to:

train the probabilistic machine learning model, wherein training the probabilistic machine learning model further comprises:

inputting training data to a machine learning algorithm, wherein the training data comprises a plurality of features correlated to a probabilistic outcome; and

training the probabilistic machine learning model as a function of the machine learning algorithm.

12. The system of claim 10 , wherein the computing device is further configured to:

train the classifying machine learning model, wherein training the classifying machine learning model further comprises:

inputting training data to a machine learning algorithm, wherein the training data comprises a plurality of features; and

training the machine learning model as a function of the machine learning algorithm.

13. The system of claim 10 , wherein interfacing conversationally further comprises:

receiving, using the computing device, a submission;

recognizing, at least a word from the submission, wherein recognizing the at least a word further comprises:

inputting the submission to a language processing model; and

recognizing the at least a word as a function of the language processing model; and

generating a response as a function of the at least a word.

14. The system of claim 13 , wherein the computing device is further configured to:

train the language processing model, wherein training the language processing model further comprises:

inputting training data to a natural language processing algorithm; and

training the language processing model as a function of the natural language processing algorithm and the training data.

15. The system of claim 10 , wherein the computing device is further configured to:

generate at least a metric, wherein generating the at least a metric further comprises:

input the intervention class to a machine learning model; and

generate the at least a metric as a function of the machine learning model.

16. The system of claim 15 , wherein the computing device is further configured to:

receive a submission from the user;

recognize at least a datum from the submission, wherein recognizing the at least a datum further comprises:

inputting the submission to a language processing model; and

recognizing the at least a datum as a function of the language processing model;

wherein the at least a datum is associated with the at least a metric.

17. The system of claim 10 , wherein the computing device is further configured to select the classifying machine learning model from a plurality of classifying machine learning models, as a function of the at least a feature, wherein the classifying machine learning model was trained using training data.

18. The system of claim 10 , wherein the computing device is further configured to:

select training data from a plurality of training data, as a function of the at least a feature; and

train the classifying machine learning model using the training data.