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Data Mining Predictive Descriptive classification regression time series analysis prediction clustering association rules summarization sequence discovery AI Machine learning Neural networks Deductive detabases
[object Object],[object Object],[object Object],Discovering useful information in large data sets
Opportunities ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],Data in many forms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tasks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Another complementary tack: Interactive visual data exploration ,[object Object],[object Object],[object Object],[object Object],[object Object],Other possibilities: converting data to sounds, etc.
Two broad approaches to Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Many techniques Fast evolving field ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
One famous technique Ross Quinlan’s ID3 algorithm
The weather data N TRUE high mild rain 14 P FALSE normal hot overcast 13 P TRUE high mild overcast 12 P TRUE normal mild sunny 11 P FALSE normal mild rain 10 P FALSE normal cool sunny 9 N FALSE high mild sunny 8 P TRUE normal cool overcast 7 N TRUE normal cool rain 6 P FALSE normal cool rain 5 P FALSE high mild rain 4 P FALSE high hot overcast 3 N TRUE high hot sunny 2 N FALSE high hot sunny 1 Class Windy Humidity Temperature Outlook Object
 
From decision trees to rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
Rules can be much more compact than trees ,[object Object],[object Object],[object Object]
From rules to decision trees ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
To learn from examples, the examples must be rich enough ,[object Object],[object Object],Importance of data preparation
Attributes ,[object Object]
Software tools ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Ad hoc methods ,[object Object],[object Object]
Term Co-occurrence Analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Interactive Data Visualization ,[object Object],[object Object],[object Object],[object Object]
 
Tree Maps ,[object Object]
Conclusion ,[object Object],[object Object],[object Object]
Baysian Networks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 
Learning a baysian network from data ,[object Object],[object Object],[object Object]
Baysian Networks   Graphical Models = Markov models undirected edges

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(Talk in Powerpoint Format)

  • 1. Data Mining Predictive Descriptive classification regression time series analysis prediction clustering association rules summarization sequence discovery AI Machine learning Neural networks Deductive detabases
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. One famous technique Ross Quinlan’s ID3 algorithm
  • 12. The weather data N TRUE high mild rain 14 P FALSE normal hot overcast 13 P TRUE high mild overcast 12 P TRUE normal mild sunny 11 P FALSE normal mild rain 10 P FALSE normal cool sunny 9 N FALSE high mild sunny 8 P TRUE normal cool overcast 7 N TRUE normal cool rain 6 P FALSE normal cool rain 5 P FALSE high mild rain 4 P FALSE high hot overcast 3 N TRUE high hot sunny 2 N FALSE high hot sunny 1 Class Windy Humidity Temperature Outlook Object
  • 13.  
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.  
  • 23.
  • 24.  
  • 25.
  • 26.
  • 27.
  • 28.  
  • 29.
  • 30. Baysian Networks   Graphical Models = Markov models undirected edges