Topic
Decision tree model
About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.
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Patent•
20 Oct 2017
TL;DR: In this paper, a decision tree model training method was proposed for determining data attributes in an OCR result, and the purpose of automatically labeling the data attributes was achieved; the consumption cost in a to-be-recognized picture recognition process was effectively reduced; and the recognition efficiency was improved.
Abstract: The invention discloses a decision tree model training method, and a method and an apparatus for determining data attributes in an OCR result. The decision tree model training method comprises the steps of obtaining a sample medical data picture, and performing OCR on the sample medical data picture to generate a first OCR result, wherein the first OCR result is a two-dimensional character string array, and each column of data in the two-dimensional character string array is used for indicating data which belongs to a same attribute column; extracting first feature information of each piece of data in the first OCR result; obtaining first labeled data corresponding to each piece of the data in the first OCR result, wherein the first labeled data is used for indicating an attribute which each piece of the data belongs to; and performing training according to the first feature information and the first labeled data to generate a decision tree model used for determining the data attributes in the OCR result. According to the method, the purpose of automatically labeling the data attributes in the recognition result is achieved; the consumption cost in a to-be-recognized picture recognition process is effectively reduced; and the recognition efficiency is improved.
2 citations
Journal Article•
TL;DR: The case study and experimental results in financial datasets show that the new algorithm can resolve the drawbacks of the traditional algorithm and could construct a suboptimal decision tree effectively.
Abstract: In order to better complete the task of classification mining on financial datasets,decision classify-entropy concept was put forward based on the rough set theory; and based on this concept,a novel decision tree construction algorithm was proposed. To overcome over-fitting,inhibiting factor was introduced to control decision tree construction. The case study and experimental results in financial datasets show that,compared with the classical C4.5 algorithm,the new algorithm can resolve the drawbacks of the traditional algorithm and could construct a suboptimal decision tree effectively. The application in financial field also proves that the new algorithm can finish the objective task much better.
2 citations
01 Jan 2013
Abstract: Natural killer (NK) cells play a key role in embryo implantation and pregnancy success, whereas blood and uterine NK expansions have been involved in the pathophysiology of reproductive failure (RF). Our main goal was to design in a large observational study a tree‐model decision for interpretation of risk factors for RF.
2 citations
2 citations
28 Dec 2020
TL;DR: In this paper, a decision tree based classification algorithm was used in the performance analysis of university physical education teachers. And the experimental results show that this algorithm can lay a foundation and provide reference for the improvement of teaching effect.
Abstract: In recent years, the level of physical education in colleges and universities is on the rise as the country attaches great importance to physical education. It is of great practical significance for the reform of physical education in China to seek ways to improve the level of physical education. The purpose of this paper is to study the application of decision tree based classification algorithm in the performance analysis of university physical education teachers. This paper introduces a decision tree data mining algorithm for teacher performance analysis and evaluation. According to the algorithm in the decision tree algorithm, a decision tree model for the analysis and evaluation of physical education teachers’ performance was constructed, and the corresponding rules were extracted. The purpose of this is to obtain the indexes needed to influence the performance of physical education teachers through the decision tree algorithm. The experimental results show that this paper can lay a foundation and provide reference for the improvement of teaching effect. Based on the evaluation of physical education teachers in a school, this paper finds that the teacher evaluation of the school is basically concentrated in the “medium” level, accounting for 70%.
2 citations