View source for Amazon technologies, inc. (20240273389). ARTIFICIAL INTELLIGENCE SYSTEM PROVIDING INTERACTIVE MODEL INTERPRETATION AND ENHANCEMENT TOOLS simplified abstract

=ARTIFICIAL INTELLIGENCE SYSTEM PROVIDING INTERACTIVE MODEL INTERPRETATION AND ENHANCEMENT TOOLS=


==Organization Name==

[[:Category:amazon technologies, inc.|amazon technologies, inc.]]


[[Category:amazon technologies, inc.]]

==Inventor(s)==

[[:Category:Shikhar Gupta of Seattle WA (US)|Shikhar Gupta of Seattle WA (US)]][[Category:Shikhar Gupta of Seattle WA (US)]]

[[:Category:Shriram Venkataramana of Seattle WA (US)|Shriram Venkataramana of Seattle WA (US)]][[Category:Shriram Venkataramana of Seattle WA (US)]]

[[:Category:Sri Kaushik Pavani of Redmond WA (US)|Sri Kaushik Pavani of Redmond WA (US)]][[Category:Sri Kaushik Pavani of Redmond WA (US)]]

[[:Category:Sunny Dasgupta of Redmond WA (US)|Sunny Dasgupta of Redmond WA (US)]][[Category:Sunny Dasgupta of Redmond WA (US)]]

==ARTIFICIAL INTELLIGENCE SYSTEM PROVIDING INTERACTIVE MODEL INTERPRETATION AND ENHANCEMENT TOOLS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240273389 titled 'ARTIFICIAL INTELLIGENCE SYSTEM PROVIDING INTERACTIVE MODEL INTERPRETATION AND ENHANCEMENT TOOLS

'''Simplified Explanation''': The abstract describes a process where an interactive interpretation session is conducted to analyze a first version of a machine learning model, identify factors influencing prediction decisions, suggest model enhancement actions, implement an enhancement action based on feedback, and store the second version of the model.

'''Key Features and Innovation''':
* Interactive interpretation session for machine learning model analysis
* Identification of factors influencing prediction decisions
* Suggestion of model enhancement actions
* Implementation of enhancement actions based on feedback
* Storage of the second version of the model

'''Potential Applications''': 
This technology can be applied in various industries such as finance, healthcare, marketing, and more to improve the accuracy and efficiency of prediction models.

'''Problems Solved''':
* Enhancing the performance of machine learning models
* Providing actionable insights for model improvement
* Streamlining the model enhancement process

'''Benefits''':
* Improved prediction accuracy
* Enhanced model performance
* Faster model iteration and enhancement

'''Commercial Applications''':
Potential commercial applications include predictive analytics software, financial forecasting tools, healthcare diagnosis systems, and marketing automation platforms.

'''Prior Art''''':
Readers can explore prior research on interactive machine learning model interpretation sessions, factors influencing prediction decisions, and model enhancement strategies in the field of artificial intelligence and machine learning.

'''Frequently Updated Research''':
Stay updated on the latest advancements in interactive machine learning model interpretation, model enhancement techniques, and factors affecting prediction decisions to enhance the understanding and application of this technology.

'''Questions about Machine Learning Model Interpretation''':
1. How does interactive interpretation improve the performance of machine learning models?
2. What are the key factors to consider when enhancing a machine learning model based on interpretation feedback?


==Original Abstract Submitted==

an interactive interpretation session with respect to a first version of a machine learning model is initiated. in the session, indications of factors contributing to a prediction decision are provided, as well indications of candidate model enhancement actions. in response to received input, an enhancement action is implemented to obtain a second version of the model. the second version of the model is stored.



[[Category:G06N5/04]]
[[Category:G06F16/28]]
[[Category:G06N20/00]]
[[Category:CPC_G06N5/04]]