[PDF] Top 20 Mining rules from an incomplete data set with a high missing rate
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Mining rules from an incomplete data set with a high missing rate
... 27 high. To deal with this disadvantage, we introduce an iterative missing-value completion method to fully infer the missing attribute values by combining an iterative mechanism ... See full document
27
Mining a Complete Set of Fuzzy Multiple-Level Rules
... association rules derived in that way are not complete, as some possible fuzzy association rules might be ...proposes a new fuzzy data-mining algorithm for extracting all possible fuzzy ... See full document
27
A DATA mining Procedure Using Neural Network- Self Organization Map and Rough Set to Discover Association Rules
... is an unsupervised two-layer network that can recognize a topological map from a random starting ...connected with each other. Each input node contributes to each output node ... See full document
8
Finding fuzzy classification rules using data mining techniques
... denotes a set consisting of the effective fuzzy classification rules obtained by s ðjÞ c ðjÞ , and W CAR and W V are relative weights of the classifi- cation accuracy rate by V ðjÞ ...fuzzy ... See full document
11
Ranking discovered rules from data mining with multiple criteria by data envelopment analysis
... ignored. A huge amount of subjective domain knowledge may exist, which can be considered as potential subjective constraints and measures for evaluat- ing association ...some rules, a data ... See full document
7
Mining Time Series Data with Fuzzy Association Rules
... Association Rules Data mining can be applied to discover the useful patterns and rules by exploring and analyzing a large quantity of ...is, a collection of data ... See full document
7
An efficient algorithm for mining temporal high utility itemsets from data streams
... of an ongoing transaction database. The deleted and added portions of an ongoing transaction database are denoted by D and D + , ...temporal high utility itemsets efficiently and ...ral high ... See full document
13
Data Mining: An Overview from A Database Perspective
... In order to conduct effective data mining, one needs to first examine what kind of features an applied knowledge dis- covery system is expected to have and what kind of chal- [r] ... See full document
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Mining Fuzzy Multiple-Level Association Rules from Quantitative Data
... and data-mining techniques have been developed to turn data into useful task-oriented ...for mining association rules identify relationships among transactions using binary values and ... See full document
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Applying Visualizing Association Rules in Medical Data Mining —An Example of Information Extraction from Severe Acute Respiratory
... Applying Visualizing Association Rules in Medical Data Mining —An Example of Information Extraction from Severe Acute Respiratory.. 中文摘要[r] ... See full document
1
Mining fuzzy generalized association rules from quantitative data under fuzzy taxonomic structures
... knowledge from data. Relevant taxonomies of data items are thus usually predefined in real-world ...applications. An item may, however, belong to different classes in different ... See full document
24
An Effective Algorithm for Mining Association Rules with Multiple Thresholds
... for mining all frequent ...the set C i of candidate i-itemsets are created by joining the frequent (i-1)-itemsets in L i-1 found in the previous ...extracted from these ...in a large number of ... See full document
12
Mining generalized fuzzy association rules from web taxonomic Mining generalized fuzzy association rules from web taxonomic
... association rules is an important data-mining task for which many algorithms have been ...present an efficient method named cluster-based fuzzy association rule (CBFAR) to discover ... See full document
6
A generic approach for mining indirect association rules in data streams
... Abstract. An indirect association refers to an infrequent itempair, each item of which is highly co-occurring with a frequent itemset called ...patterns from streaming data. In ... See full document
10
Combined Association Rules for Dealing with Missing Values
... 摘要: With the rapid increase in the use of databases, the problem of missing values inevitably ...these missing values effectively should be highly precise in order to estimate the missing ... See full document
1
Maintenance of Association Rules in Data Mining
... itemsets with the previously retained large and pre-large ...If a candidate 1-itemset from the newly inserted transactions is also among the large or pre-large 1-itemsets from the original ... See full document
6
Using Affinity Set and Data Mining on Revisiting Rules of Emergent Patients 李宗鴻、陳郁文
... Data mining can explore the hidden messages from data for ...is a very important ...example、Affinity Set、Back-propagation Neural Network、Rough Set theory、Support Vector ... See full document
3
Mining Frequent Itemsets from Data Streams with a Time-Sensitive Sliding Window
... Abstract Mining frequent itemsets has been widely studied over the last ...on mining frequent itemsets from static ...applications, data flow through the Internet or sensor ...the ... See full document
12
Fuzzy data mining for interesting generalized association rules
... Transactions with quantitative values and items with hierarchy relation are, however, commonly seen in real-world ...of mining generalized association rules for quantitative ...generalized ... See full document
33
Elicitation of classification rules by fuzzy data mining
... j A TRg; ð10Þ where TR is the set of fuzzy rules generatedby the proposed ...adaptive rules are further employed to adjust the fuzzy confidence of R b : If t p is correctly classifiedthen FC(R b ... See full document
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