A Research Study On Machine Learning Community, The Decision Tree Algorithms, Quinlan 's Id3 And Its Successor Essay

1462 WordsJan 11, 20166 Pages
Many researchers have proposed various methodologies for finding best solution. J. Ross Quinlan. In machine learning community, the decision tree algorithms, Quinlan’s ID3 and its successor C4.5: Programs for machine learning are probably the most popular. The various issues related to decision tree are discussed from the initial state of building a tree to methods of pruning, converting trees into rules and handling other problems such as missing attribute values. Apart from that, Quinlan discusses limitations of programs for machine learning, such as its bias in favour of rectangular regions along with ideas for extending the abilities of algorithm. [1] Mohamed Medhat Gaber, Arkady Zaslavsky and Shonali Krishnaswamy. Illustrated that the theoretical foundations of data stream analysis discussed. Mining data stream systems, techniques are critically reviewed. Finally, the research problems in streaming mining field of study are discussed. These research issues should be addressed in order to realize robust systems that are capable of fulfilling the needs of data stream mining applications. The main aim is to explore the data for testing a specific hypothesis. The machine learning field came into existence with advancement in computing power. So, the goal is to achieve efficient solutions to data analysis problems. There are some issues regarding data stream mining discussed such as ‘Handling the continuous flow of data streams.’, ‘Unbounded

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