17529316. CLASS PREDICTION BASED ON CLASS ACCURACY OF MULTIPLE MODELS simplified abstract (International Business Machines Corporation)

From WikiPatents
Jump to navigation Jump to search

CLASS PREDICTION BASED ON CLASS ACCURACY OF MULTIPLE MODELS

Organization Name

International Business Machines Corporation

Inventor(s)

Suvedhahari Velusamy of Coimbatore (IN)

Sathya Santhar of Ramapuram (IN)

Kothagorla Lakshmana Rao of Chirala (IN)

Sridevi Kannan of Chennai (IN)

CLASS PREDICTION BASED ON CLASS ACCURACY OF MULTIPLE MODELS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17529316 titled 'CLASS PREDICTION BASED ON CLASS ACCURACY OF MULTIPLE MODELS

Simplified Explanation

The patent application describes a method, computer program product, and computer system for predicting the class of a given input using multiple models. The process involves receiving class parameters of the models and using them to predict the class of the input.

  • The method predicts the class of a given input using multiple models.
  • Class parameters of the models are received as input.
  • The process can be a model ensemble process, where the class of the input is predicted by selecting a class that maximizes a function of class accuracy parameters.
  • The process can also involve a first threshold process, where the class of the input is predicted by running a model with a class accuracy parameter above a specified threshold.
  • Alternatively, the process can involve a second threshold process, where a specified class is predicted by running all models with a class accuracy parameter above the specified threshold.

Potential Applications

  • This technology can be applied in various fields where classification of inputs is required, such as image recognition, natural language processing, and fraud detection.
  • It can be used in recommendation systems to predict user preferences based on multiple models.
  • This method can be utilized in medical diagnosis to predict the class of a patient's symptoms based on different models.

Problems Solved

  • The technology solves the problem of accurately predicting the class of a given input by utilizing multiple models and their class parameters.
  • It addresses the challenge of selecting the most accurate model or combination of models for predicting the class of an input.

Benefits

  • The method improves the accuracy of class prediction by considering multiple models and their class parameters.
  • It provides flexibility in selecting the prediction process, allowing for model ensembles or threshold-based approaches.
  • This technology can be easily implemented in existing computer systems and can be applied to various domains.


Original Abstract Submitted

A method, computer program product, and computer system for predicting a class of a given input to multiple models. Class parameters of the models are received. A process that predicts the class of a given input to the models is performed using the class parameters of the models. The process is (i) a model ensemble process predicting that the class of the given input is a class that maximizes a function of class accuracy parameters selected from combinations of the class parameters, (ii) a first threshold process based on a requirement that the class of the given input be predicted by running a model whose class accuracy parameter is at least a specified threshold, or (iii) a second threshold process based on a requirement that a specified class be predicted by a running of all models whose class accuracy parameter is at least the specified threshold.

Retrieved from "http://wikipatents.org/index.php?title=17529316._CLASS_PREDICTION_BASED_ON_CLASS_ACCURACY_OF_MULTIPLE_MODELS_simplified_abstract_(International_Business_Machines_Corporation)&oldid=23531"