翻訳と辞書 Words near each other ・ Rules (restaurant) ・ Rules (song) ・ Rules and Meanings ・ Rules and Referee Committee ・ Rules and Regulations ・ Rules and Regulations (Roll Deep album) ・ Rules and Regulations (song) ・ Rules and regulations for God-heads (Ayyavazhi) ・ Rules Changed Up ・ Rules Committee (Georgia House) ・ Rules Committee (Georgia Senate) ・ Rules Compendium ・ Rules derby ・ Rules Don't Stop ・ Rules Enabling Act ・ Rules Extraction System Family ・ Rules for Archival Description ・ Rules for Radicals ・ Rules for the Direction of the Mind ・ Rules lawyer ・ Rules of Acquisition ・ Rules of Attraction (Elkeles novel) ・ Rules of basketball ・ Rules of chess ・ Rules of Civility and Decent Behaviour In Company and Conversation ・ Rules of cribbage ・ Rules of Dating ・ Rules of Deception ・ Rules of Decision Act ・ Rules of engagement Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Rules Extraction System Family ： ウィキペディア英語版 Rules Extraction System Family Rules Extraction System (RULES) is one family of inductive learning that include several covering algorithms. This family is used to build a predictive model based on given observation. It works based on the concept of separate-and-conquer to directly induce rules from a given training set and build its knowledge repository. Algorithms under RULES family are usually available in data mining tools, such as KEEL and WEKA, known for knowledge extraction and decision making. == Overview == RULES family algorithms are mainly used in data mining to create a model that predicts the actions of a given input features. It goes under the umbrella of inductive learning, which is a machine learning approach. In this type of learning, the agent is usually provided with previous information to gain descriptive knowledge based on the given historical data. Thus, it is a supervised learning paradigm that works as a data analysis tool, which uses the knowledge gained through training to reach a general conclusion and identify new objects using the produced classifier. Inductive learning had been divided into two types: Decision Tree (DT) and Covering Algorithms (CA). DTs discover rules using decision tree based on the concept of divide-and-conquer, while CA directly induces rules from the training set based on the concept of separate and conquers. Although DT algorithms was well recognized in the past few decades, CA started to attract the attention due to its direct rule induction property, as emphasized by Kurgan et al. (). Under this type of inductive learning approach, several families have been developed and improved. RULES family (), known as RULe Extraction System, is one family of covering algorithms that separate each instance or example when inducing the best rules. In this family, the resulting rules are stored in an ‘IF condition THEN conclusion’ structure. It has its own induction procedure that is used to induce the best rules and build the knowledge repository. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Rules Extraction System Family」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.