Application Of Machine Learning In Management Decision Of Listed Companies

In the process of production and operation,enterprises will produce a large amount of data,which also contains certain enterprise operation information.In order to survive and develop in the highly competitive market environment,enterprises need to analyze these production and operation data to obtain effective information and assist enterprises to make scientific and reasonable operation decisions.However,with the increase of the number of enterprises and business data,the traditional business analysis methods are no longer applicable.Therefore,how to use efficient analysis methods to mine effective information in a large number of business data and provide basis for enterprise adjustment and business decision-making has become a problem that enterprise operators and managers need to pay attention to.With the advent of the era of big data,big data processing technology has been developed,and the traditional data processing and analysis methods have gradually changed.Among them,machine learning related algorithms have been applied to many fields because of their fast and efficient processing ability and scientific and accurate processing results.However,there are few literatures on the application of machine learning related algorithms in enterprise management in China,and the existing literatures also have some limitations in enterprise management analysis and decision-making.Therefore,on the basis of reading the literature research at home and abroad,this paper takes the Shanghai and Shenzhen A-share listed companies in the software and information technology service industry as the research case,takes improving the enterprise value creation ability as the business goal,and uses the clustering algorithm to classify the sample companies in multiple categories to refine the level of enterprise business objectives.Finally,the paper constructs the decision tree model through the cart decision tree algorithm to mine the indicators with strong relevance to the enterprise business objectives,Provide enterprises with key indicators and their adjustable range that need to be concerned to achieve business objectives.This paper applies machine learning algorithm to business analysis and decision-making,provides high-speed and convenient algorithm support for business decision-making,reduces the investment of human cost,and improves the use efficiency of business data.This paper uses the indicators that reflect the overall business activities and achievements of enterprises to build a business index system,which makes up for the deficiency of the existing literature that mostly explores the application of machine learning algorithm in enterprise business decision-making from a single business perspective;The clustering algorithm is used to classify enterprises into multiple classes,which provides algorithm support for the business objectives of enterprises to be divided into multiple levels;Finally,through the decision tree model,the paper excavates the indicators with strong correlation with the enterprise’s business objectives,visually displays the key impact indicators and their adjustable range of different enterprise value creation ability in the form of tree diagram,gives people intuitive and easy to understand analysis results,and finally provides a new research idea for enterprises to improve their value creation ability.