Method and system for performing prediction using composite machine learning model

A machine learning model and model technology, applied in the field of training compound machine learning models, can solve the problem that machine learning models cannot be well applied, and achieve the effect of comprehensive machine learning effect.

Pending Publication Date: 2021-10-29
THE FOURTH PARADIGM BEIJING TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Exemplary embodiments of the present invention aim to overcome the defect that a single machine learning model cannot be well adapted to the characteristics of different situations

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  • Method and system for performing prediction using composite machine learning model
  • Method and system for performing prediction using composite machine learning model
  • Method and system for performing prediction using composite machine learning model

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Embodiment Construction

[0142] In order to enable those skilled in the art to better understand the present invention, exemplary embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific implementation methods.

[0143] Machine learning is an inevitable product of the development of artificial intelligence research to a certain stage. It is committed to improving the performance of the system itself by means of calculation and using experience. In computer systems, "experience" usually exists in the form of "data". Through machine learning algorithms, "models" can be generated from data. Model, when faced with a new situation, the model will provide the corresponding judgment, that is, predict the result. Machine learning can be implemented in the form of "supervised learning", "unsupervised learning" or "semi-supervised learning". Make certain restrictions. In addition, it should also be noted that in the process of tr...

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Abstract

Provided are a method and system for performing prediction using a composite machine learning model. The composite machine learning model comprises at least two types of sub-models. The method comprises: (A) obtaining a prediction data record; (B) generating a plurality of feature subsets of prediction samples corresponding to the prediction data records based on attribute information of the prediction data records; and (C) providing the plurality of feature subsets of the prediction sample for sub-models included in the composite machine learning model to obtain a prediction result of the composite machine learning model for the prediction sample, wherein, in the composite machine learning model, the sub-models are trained according to a gradient lifting framework. In this way, various types of sub-models can be effectively fused for cooperative work, and the advantages of the sub-models are fully played to obtain a good comprehensive machine learning effect.

Description

[0001] This application is a divisional application of a patent application with an application date of May 05, 2017, an application number of 201710311433.2, and a patent application entitled "Method and System for Prediction Using a Composite Machine Learning Model". technical field [0002] Exemplary embodiments of the present invention relate generally to the field of artificial intelligence, and more particularly, to a method and system for performing prediction using a composite machine learning model and a method and system for training a composite machine learning model. Background technique [0003] With the emergence of massive data, artificial intelligence technology has developed rapidly, and in order to mine value from massive data, it is necessary to generate training and / or prediction samples suitable for machine learning based on data records, so as to help train machines Learn a model and / or leverage a trained machine learning model to perform predictions. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N20/00G06N5/02G06Q10/04
CPCG06N5/022G06N20/00G06Q10/04
Inventor 杨强戴文渊陈雨强郭夏玮涂威威
Owner THE FOURTH PARADIGM BEIJING TECH CO LTD
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