Data Mining Ch 1.1-1.5

Data Mining Ch 1.1-1.5

1. Wealth/availability of information

   • stored electronically through world wide web
   • applying to customers
     • future interest in products
     • buying trends
     • discovering patterns

2. structural patterns

   • sets of rules that classify decisions
     • decision trees
     • all combos of outcomes

3. Machine Learning

   • stats
     • more than hypothesis testing
   • gain knowledge
   • receive instruction
   • to be/stay informed and become aware of information
   • domain knowledge rule for malformation and formation

4. Real Life Datasets

   • often proprietary due to companies not wanting to share exact info
   • characterizes by features
     • ex: weather-windy, outlook, hot/mild, cold, temperature, etc
   • contact lenses
     • age of patient
     • rate of tear production
     • precription
     • what lenses needed with astigmatism?
   • CPU performances
     • central processing unit using regression analysis

5. Web Mining

   • hyperlinks to rank websites for SEO
   • search engines mine content of web like social media
   • photos, movies, tv shows, books etc
   • screening imaged to detect future implications
   • load forecasting model for year with 3 components
   • market basket analysis

6. statistics + marketing