Research on Machine Learning Algorithm in Large Data Environment

Objective: To study the algorithm of machine learning in large data environment. Methods: using the divide and conquer strategy and parallel algorithm. Process: feature selection, classification, clustering and association analysis of large data. Results and analysis: from the experimental results, we can see, using the divide and conquer strategy and parallel algorithm, we can extract information which is hidden but valuable from large data, improve analysis and problem solving skills. This result is obtained because of the algorithm can effectively extract, retrieve, store, share, analyze and deal with complex structure and large amount of data. Conclusion: the divide and conquer strategy and parallel algorithm for large data on machine learning algorithm to actively promote around is effective, and maximize the value of the data.