Automated machine learning tool for explaining the effects of complex text on predictive results

A system for explaining text from predictive results generated by at least one algorithmic model, the system comprising:

• a feature engineering module configured by a processor to:
• create a plurality of vectors for at least one string variable, with each string variable comprising identified text, each vector created comprising a numeric combination, each numeric combination identifying a variable name and at least one selected from a group comprising a value having a word and another value having a phrase;
• a predictive engine module configured by the processor to:
• generate at least one predictive result using the at least one algorithmic model, the data set, and the vectors created, the predictive results comprising the at least one string variable or a modified version of the at least one string variable and at least one confidence score associated with the at least one string variable or the modified version of the at least one string variable;
• a text explanation module configured by the processor to:
• map at least one selected from a group comprising words and at least one phrase from qualified text of the at least one string variable to the numeric combinations of the vectors;
• determine a probability score for each word and each phrase;
• and
• generate chart variables and plot variables, the plot variables comprising at least one of selected from a group comprising the most influential words and the most influential phrases, the most influential words and phrases based on the probability scores.

A method for explaining text from predictive results generated by at least one algorithmic model, the method comprising:

• creating a plurality of vectors for at least one string variable, with each string variable comprising identified text, each vector created comprising a numeric combination, each numeric combination identifying a variable name and at least one selected from a group comprising a value having a word and another value having a phrase;
• generating at least one predictive result using the at least one algorithmic model, the data set, and the vectors created, the predictive results comprising the at least one string variable or a modified version of the at least one string variable and at least one confidence score associated with the at least one string variable or the modified version of the at least one string variable;
• mapping at least one selected from a group comprising words and at least one phrase from qualified text of the at least one string variable to the numeric combinations of the vectors;
• determining a probability score for each word and each phrase;
• and
• generating chart variables and plot variables, the plot variables comprising at least one of selected from a group comprising the most influential words and the most influential phrases, the most influential words and phrases based on the probability scores.