Notes:

• We're basically making the attributes to be used for the decision tree instead of using a decision tree algorithm

• There’s a max # of stories for a wooden frame so we need to find that number

• Know columns A-E, find column G

• ? = Defining data point

• Use data points from things like sqft, zip code, etc. from the exec section to guess attributes in sections 4 and 5

• Type of elevator is determined by stories

• Primary: Confirm or disconfirm Bruce’s hypotheses

  • These hypotheses take input from “Executive Summary” (dataset to be given by eod tomorrow) and output to Sections 4 and 5

• Secondary: “Bottom-up approach”, i.e. finding other correlations, possibly with features that are found in other sections. 

  • Will need additional datasets to do this 

• Climate Zones for reference: 

  • https://xp20.ashrae.org/standard169/169_2013_a_20201012.pdf 

  • https://www.energyvanguard.com/wp-content/uploads/2013/04/IECC-climate-zone-map_Revised_9.jpg