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Association rules mining

Xem 1-20 trên 29 kết quả Association rules mining
  • In this paper, we propose a novel framework for mining security events of DARPA-2009 network intrusion detection dataset. Our approach relies on finding a correlation between the security event of the dataset and the destination port that is exploited by an attacker in order to hack the network according to what security event reports. Association rule mining technique has been used in this paper to discover such correlation, since it is widely used to find strong correlations between features of massive datasets in terms of generated rules.

    pdf7p byphasse043256 23-03-2019 3 0   Download

  • Association rules represent a promising technique to find hidden patterns in a medical data set. The main issue about mining association rules in a medical data set is the large number of rules that are discovered, most of which are irrelevant. Such number of rules makes search slow and interpretation by the domain expert difficult. In this work, search constraints are introduced to find only medically significant association rules and make search more efficient.

    pdf8p lebronjamesuit 23-08-2012 49 6   Download

  • Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Retrovirology Research cung cấp cho các bạn kiến thức về ngành y đề tài:"Discovery of novel targets for multi-epitope vaccines: Screening of HIV-1 genomes using association rule mining...

    pdf12p toshiba14 24-10-2011 26 2   Download

  • This paper proposes a method for mining fuzzy association rules using compressed database. We also use the approach of Hedge Algebra (HA) to build the membership function for attributes instead of using the normal way of fuzzy set theory. This approach allows us to explore fuzzy association rules through a relatively simple algorithm which is faster in terms of time, but it still brings association rules which are as good as the classical algorithms for mining association rules.

    pdf12p dieutringuyen 07-06-2017 19 1   Download

  • This paper presents a new proposal model of predictor using FAR to elevating prediction performance and avoids extraction of the fixed set of FAR before prediction progress. Indeed, a modification tree structure of a FP-growth tree is used in fuzzy frequent itemset mining, when a new requirement raised, the proposed algorithm mines directly in the tree structure for the best prediction result.

    pdf10p jangni 13-04-2018 10 1   Download

  • User preference is very important in orienting data miner, and this is the reason why these user preferences are integrated in the mining process, where they are coupled with Association Rules Mining “ARM” Algorithms to select only Association Rules “ARs” that satisfy the user’s wishes and expectations.

    pdf11p vithanos2711 09-08-2019 4 0   Download

  • The present paper focuses on the discovery of association rules in which the left-handed and right-handed sides contain in two user-supplied maximum single constraints. If the constraints appear on or differ from a lattice of closed itemsets (together with their typically undersized generators and supports) that have been mined and saved once, we quickly extract the corresponding frequent sub one.

    pdf17p vithanos2711 09-08-2019 4 0   Download

  • In this paper, we propose an approach to discover a category of relevant association rules based on multi-criteria analysis. In other side, the general process of association rules extraction becomes more and more complex, to solve such problem, we also proposed a multi-agent system for modeling the different process of our proposed approach.

    pdf11p vititan2711 13-08-2019 0 0   Download

  • Chapter 2: Data Mining includes about Overview of data mining, Association rules, Classification, Regression, Clustering, Other Data Mining problems, Applications of data mining.

    ppt154p cocacola_10 08-12-2015 26 4   Download

  • Given a set of transactions, find rules that will predict the occurrence of an item based on the occurrences of other items in the transaction. Given a set of transactions T, the goal of association rule mining is to find all rules having support ≥ minsup threshold confidence ≥ minconf threshold Brute-force approach: List all possible association rules Compute the support and confidence for each rule Prune rules that fail the minsup and minconf thresholds  Computationally prohibitive!...

    ppt82p trinh02 18-01-2013 38 3   Download

  • The paper proposes an equivalence relation using the closure of itemset to partition the solution set into disjoint equivalence classes and a new, efficient representation of the rules in each class based on the lattice of closed itemsets and their generators. The paper also develops a new algorithm, called MAR-MINSC, to rapidly mine all constrained rules from the lattice instead of mining them directly from the database.

    pdf17p vititan2711 13-08-2019 0 0   Download

  • In recent researches, many approaches based on association rules have been proposed to improve the accuracy of recommender systems. These approaches are primarily based on Apriori data mining algorithm in order to generate the association rules and apply them to improving the recommendation results.

    pdf16p thuyliebe 05-10-2018 3 0   Download

  • Chapter 12 - Pattern and rule assessment. In this chapter we discuss how to assess the significance of the mined frequent patterns, as well as the association rules derived from them. Ideally, the mined patterns and rules should satisfy desirable properties such as conciseness, novelty, utility, and so on. We outline several rule and pattern assessment measures that aim to quantify different properties of the mined results.

    ppt40p thiendiadaodien_4 08-01-2019 7 0   Download

  • The model parameters were configured and justified using actual data collected in two years 2008-2009. The results showed the accuracy of the model for CPI forecast in Vietnam and the model can also be used to predict the price changes of merchandises.

    pdf12p minhxaminhyeu3 25-06-2019 1 0   Download

  • 4.2.3 MTMF MTMF combines the best parts of the Linear Spectral Mixing model and the statistical Matched Filter model while avoiding the drawbacks of each parent method (Boardman, 1998). It is a useful Matched Filter method without knowing all the possible endmembers in a landscape especially in case of subtle, sub-pixel occurrences. Firstly, pixel spectra and endmember spectra require a minimum noise fraction (MNF) (Green et al., 1988, Boardman, 1993) transformation. MNF reduces and separates an image into its most dimensional and non-noisy components.

    pdf464p lulanphuong 22-03-2012 133 43   Download

  • Data Mining with Association Rules - 4,1 Khi kết hợp nguyên tắc phân tích hữu ích? Một sức hấp dẫn của phân tích thị trường xuất phát từ sự rõ ràng và tiện ích của kết quả của nó, mà trong các hình thức của luật kết hợp. Có một hấp dẫn trực quan để phân tích thị trường bởi vì nó thể hiện sản phẩm hữu hình và các dịch vụ liên quan đến nhau, làm thế nào họ có xu hướng nhóm với nhau. Một nguyên tắc giống như, "nếu một khách hàng mua ba cách gọi điện...

    pdf12p hoatuongvihong 02-11-2011 39 9   Download

  • ITARM - Incremental Temporal Association Rules Mining dựa trên nền của thuật toán Sliding-Window Filtering, duy trì những tập tập phổ biến sau khi dữ liệu đã được cập nhật. Cùng tìm hiểu thuật toán này qua bài tiểu luận Thuật toán hiệu quả trong việc khai thác những luật kết hợp thời gian - ITARM.

    pdf20p wave_12 05-04-2014 44 7   Download

  • Data warehouses usually have some missing values due to unavailable data that affect the number and the quality of the generated rules. The missing values could affect the coverage percentage and number of reduces generated from a specific data set. Missing values lead to the difficulty of extracting useful information from data set. Association rule algorithms typically only identify patterns that occur in the original form throughout the database.

    pdf6p giacattan 05-01-2013 34 5   Download

  • One of the main reasons for choosing ARC is for its superior ability at handling imbalanced class distributions. It utilizes the association rule mining, making sampling unnecessary in many cases otherwise requiring sampling. In [WZYY05], ARC has been shown to produce the best result among many algorithms on the data set used for KDD- 98 [Kdd98], which has a skewed class distribution. In addition, ARC can handle high dimensionality (the data set has more than 400 variables) without a considerably long running time.

    pdf34p lenh_hoi_xung 21-02-2013 42 4   Download

  • Transform categorical attribute into asymmetric binary variables Introduce a new “item” for each distinct attribute-value pair Example: replace Browser Type attribute with Browser Type = Internet Explorer Browser Type = Mozilla Browser Type = Mozilla

    ppt67p trinh02 18-01-2013 32 3   Download

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