資料探勘
Overview
| Works: | 233 works in 84 publications in 84 languages | |
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Titles
部分多重週期性無重複樣式的有效率探勘方法 = = Efficient Partial Multiple Periodic Patterns Mining Without Redundant Rules /
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利用多層高度平衡交易樹探勘頻繁樣型 = = frequent pattern mining using mul-level AVLtransaction trees /
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資料探勘 : = 人工智慧與機器學習發展以SPSS Modeler為範例 = Data mining : artificial intelligence and machine learning development /
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一個新的具有離群值偵測能力的分群演算法 = = AIRO : A New Data Clustering Algorithm with the Ability of Identifying the Outliers /
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利用option node技巧的決策樹合併演算法之研究 = = The Combination of Decision Trees Using Option Node /
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於資料串流環境下之知識探索中式樣興趣度增長之研究 = = The PIG: A Study of Pattern's Interestingness Growth in Knowledge Discovery of Data-Streaming Environment /
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資料探勘理論與應用 = = Data mining theories and applications : 以IBM SPSS Modeler為範例 : in case of IBM SPSS modeler /
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大數據 : = 知識經濟與實務應用 = Big data : the data wisdom and knowledge-based economies /
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數據挖掘 : = 實用機器學習工具與技術 = Data mining : practical machine learning tools and techniques /
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應用隨機森林演算法於花蓮地區交通事故嚴重度主要影響因子研究 = = Exploring the Dominant Factors Influencing Traffic Accident Severity in Hualien County Using Random Forest Algorithm /
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一種用於能源互聯網的排放感知日前電力調度系統 = = An emission-aware day-ahead power scheduling system for internet of energy /
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資料探勘技術應用於網路入侵偵測特徵值搜尋之研究 = = DATA MINING TECHNIQUES FOR SIGNATURE SEARCH IN NETWORK INTRUSION DETECTION /
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大數據分析與應用實戰 : = 統計機器學習之資料導向程式設計 = Pragmatic big data analytics : statistical machine learning through data-driven programming /
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以機器學習方法分析財務報表操控之研究 = = Analyzing financial statement manipulation by using machine learning /
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高效率比例性容錯資料探勘演算法 = = An Efficient Algorithm for Proportionally Fault-tolerant Data Mining /
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在平行分散式環境下有效的探勘部分多重週期性型樣 = = A Parallel Algorithm for Partial Multiple Periodic Patterns Mining with Minimum Inter-Processor Communication /
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序列型態應用於疾病分類碼之分析研究 = = A Research on Novel Knowledge Retrieval from ICD9 Sequences /
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在醫學報告資料中探勘連續序列 = = Mining Useful Sequential patterns from Medical Data /
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資料探勘在股市序列型樣的應用 = = A Novel Data Mining Technique for Stock Market Analysis /
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多重最小支持度關聯規則探勘演算法之醫療檢驗應用 = = Multiple Minimum Support Association Rule Mining for Hospitalization Prediction of Hemodialysis Patients : 以血液透析病患之住院預測為例 /
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於關聯規則探勘上隱藏敏感知識之新式演算法 = = A Novel Method for Protecting Sensitive Knowledge in Association Rules Mining /
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在負相關下考慮產品間的替代關係 = = Negative association rules analysis by considering substitution relationship between products /
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於多資料串流中序列式樣探勘之單一性通過演算法 = = A Single Pass Algorithm for Mining Sequential Patterns Across Online Data Streams /
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偵測資料串流上頻率震動項目之單一通過演算法 = = A Single Pass Algorithm of Finding Frequent Vibrated Items over Online Data Streams /
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一個新式跨層次關聯規則探勘之演算法 = = A Bottom Up Algorithm for Mining Cross-Level Association Patterns without Redundant Rules Generation /
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在大型資料庫中探勘資料項目間之強替代性規則 = = Mining Strong Substitution Rules between Sets of Items in Large Database /
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以容錯關聯圖為架構探勘固定式及比例式容錯高頻式樣 = = Mining Fixed and Proportional Fault-Tolerant Frequent Patterns Efficiently by FT-association graph /
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在多資料串流中利用遞增式更新之序列式樣探勘 = = Incremental Update Of Sequential Pattern Mining On Data Streams /
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運用資料探勘技術建構顧客流失行為預測模型 = = An Application of Data Mining for Constructing Customers' Attrition Predicting Model - An Example of Bank's Credit Card Operation : 以國內某銀行信用卡顧客為例 /
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文字探勘在科技政策研究之應用 = = The application of text mining for science and technology policy research /
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使用黎曼ζ函數模型於線上資料改變之偵測 = = Riemann Zeta Function Model for Online Data Change Detection /
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利用二元整數規劃演算法解決敏感式樣隱藏問題 = = Solving Sensitive Itemset Hiding Problem by Using Binary Integer Programming Method with Minimal Side Effects /
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在資料串流環境中探勘熱銷週期模型之研究 = = Bursty items detection and hot period modeling in an online stream environment /
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大數據時代 = = Big data revolution : how data science changes the world /
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R語言 : = 量表編製、統計分析與試題反應理論 = R programming language for scale development, statistical analysis and item response theory /
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Kaggle競賽 : = 預測分子性質 = Kaggling predicting molecular properties competition /
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電動車路徑及充電規劃與電網電力調度整合系統 = = Coordinated electric vehicle charging and power scheduling for the internet of energy /
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以天氣資訊結合資料探勘技術預測藥品耗用量 = = Prediction drug consumption by using climate information and data mining techniques /
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