an extended two-phase architecture for mining time series data
TRANSCRIPT
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An Extended Two-Phase Architecture for Mining Time Series Data
An-Pin, Chen; Yi-Chang, Chang; Nai-Wen, Hsu
{apc, ycchen, sosorry}@iim.nctu.edu.tw
2005 KES@Melbourne
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APC Laboratory
Financial Investment DecisionIntelligent Decision Support SystemExpert System
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Time series data
Vary with time…
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If we could…
Forecast Get quantitative result Validate the forecast result
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Outline
Literature review Two-phase architecture Experiment result Conclusion
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Literature review
Time series analysis Pattern recognition, Similarity measure
Disadvantage Non-quantitative result, Non-statistical meaning
Association rule mining Advantage
Inference result: (If A Then B) Disadvantage
Either too many or too few rules The wide range rules
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The Concept of Two-phase architecture
How to enforce the effectiveness of rules? Do EDA before association rule mining
How to eliminate the low predictability rules? Calculate the accuracy after association rule mining
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Association rule mining process
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Association rule mining process
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Association rule mining process
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Traditional association rule mining for time series data
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Traditional association rule mining for time series data
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Traditional association rule mining for time series data
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Exploratory data analysis
What can EDA do? maximize insight into a data set determine optimal factor settings
What does EDA contain?
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Two-phase architecture
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Experiment target Taiwan Weighted Stock Index trading
volume Totally 480 days Each day includes 270 ticks
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Experiment result & comparison
3 criteria The number of rules The accuracy of rules The effectiveness of rules
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Conclusion Two-phase architecture mining is superior than
tradition architecture mining by The number of rules The accuracy of rules The effectiveness of rules
Some better clustering algorithms may be adopted in the future
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Thanks for your attention…
Q & A
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Appendix A :An example of time series data
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Raw data in database
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Phase 1:Exploratory data analysis (EDA)
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Kernel smoothing
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Phase 2:Quantitative inter-transaction association rules
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Accuracy Analysis
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Accuracy Analysis
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Accuracy Analysis