MR - Random Forest Algorithm for Distributed Action Rules Discovery
نویسندگان
چکیده
منابع مشابه
Mr – Random Forest Algorithm for Distributed Action Rules Discovery
Action rules, which are the modified versions of classification rules, are one of the modern approaches for discovering knowledge in databases. Action rules allow us to discover actionable knowledge from large datasets. Classification rules are tailored to predict the object’s class. Whereas action rules extracted from an information system produce knowledge in the form of suggestions of how an...
متن کاملDiscovery of Classification Rules using Distributed Genetic Algorithm
This paper presents a distributed genetic algorithm for the discovery of classification rules. Population is contained in the form of interconnected demes. The local selection and reproduction mechanism is used to evolve the species within demes, and diversity is enhanced by migrating rules among some of the selected demes. Subsumption operator has been finally applied to reduce the complexity ...
متن کاملTree-Based Algorithms for Action Rules Discovery
One of the main goals in Knowledge Discovery is to find interesting associations between values of attributes, those that are meaningful in a domain of interest. The most effective way to reduce the amount of discovered patterns is to apply two interestingness measures, subjective and objective. Subjective measures are based on the subjectivity and understandability of users examining the patte...
متن کاملDiscovery of Interesting Action Rules
There are two aspects of interestingness of rules, objective and subjective measures ([7], [1], [15], [16]. Objective measures are datadriven and domain-independent. Generally, they evaluate the rules based on their quality and similarity between them. Subjective measures are user-driven, domain-dependent, and include unexpectedness, novelty and actionability [7], [1], [15], [16]. Liu [7] defin...
متن کاملA Random Forest Classifier based on Genetic Algorithm for Cardiovascular Diseases Diagnosis (RESEARCH NOTE)
Machine learning-based classification techniques provide support for the decision making process in the field of healthcare, especially in disease diagnosis, prognosis and screening. Healthcare datasets are voluminous in nature and their high dimensionality problem comprises in terms of slower learning rate and higher computational cost. Feature selection is expected to deal with the high dimen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Data Mining & Knowledge Management Process
سال: 2016
ISSN: 2231-007X,2230-9608
DOI: 10.5121/ijdkp.2016.6502