| With the rapid development of computer technology,data mining has gradually become the focus of people's attention.Data mining algorithms commonly used in association rules mining algorithm,in which the Apriori algorithm is the most classic.Firstly,the data are collected and processed,and the algorithm obtains the relevance between data through analysis,and visualize the mining results,which has been widely applied in various fields.At present,the basketball game has become one of the most important events at home and abroad.How to get the optimal combination of basketball players and how to arrange tactics has become a key factor in the development of the domestic basketball industry.Using the data of the basketball game related data mining,and then find out the correlation of data,according to the result of data mining,we can further conclude that the optimal combination of basketball players has become particularly important for coaches to provide decision support.Firstly,this paper introduces related knowledge in data mining,and focuses on the idea of combining basketball players' data analysis with association rules mining technology.Extract the hidden in the basketball game behind the valuable data information by Apriori algorithm of association rules,according to the basketball game players between the match with each other and obtain the score data,dig out the basketball team with the strong association rules of reliability,and the analysis shows that the optimum combination of basketball players.In order to improve the efficiency of the algorithm,this paper makes some improvements to the Apriori algorithm.In this paper,the idea of combining the lower triangular support matrix with the vector is proposed,which aims at improving the efficiency of generating frequent 2-itemsets and ensuring the effectiveness of the strong association rules among the basketball players.The results show that based on the experimental data that the basketball players cooperate with each other and score and compared with the L-Apriori algorithm,it is found that the L-Apriori algorithm has better performance than the traditional Apriori algorithm under the same support degree threshold with different database transaction number and the same database transaction number with different support thresholds.At the same time,the L-Apriori algorithm is applied to optimize the combination of basketball players,according to the minimum support threshold and a minimum confidence threshold can optimize the basketball team strong association rules mining in combination effectively,so as to achieve the desired effect.Based on the above theoretical analysis and experimental results,this paper will lay a good foundation for the further research on the optimal combination of basketball players in the future. |
