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RF - Insight 2015 - Demo

  1. 1. Greentoe Consulting Project Romano Foti - Insight 2015
  2. 2. Motivation Offer the user a tool to assess the probability of success of an auction bid Objective Improve the accuracy of the current gauge
  3. 3. Starting Simple: Algorithms Comparison 2-Category classification problem: 1) Offer acceptance 2) Offer rejection Logistic Regression: 6-Fold Cross-Validation ROC Random Forest Gradient Boosting Naive Bayes
  4. 4. Incorporating counter-offers 3-Category classification problem: 1) Offer acceptance 2) Offer rejection 3) Counter-offer Precision Recall Expired 0.69 0.71 Accepted 0.56 0.50 Counter Offer 0.61 0.61 Avg/Tot 0.64 0.64 Precision Recall Expired 0.64 0.65 Accepted 0.42 0.70 Counter Offer 0.58 0.41 Avg/Tot 0.58 0.56 Random Forest: Multi-Class ROCLogistic Regression: Multi-Class ROC
  5. 5. Final Product Logistic Regression Model How is this going to help Greentoe Greentoe will use my codebase to improve the accuracy of the model and provide more refined customer feedback More accurate gauge More trust More customers Fast Interpretable Flexible
  6. 6. About Me Bioluminescence Vulnerability of water supply to climate change ConstructionsConstructions PhD Impact of climate and humans on the Everglades Urban GI performance PhD and Post-doc research work
  7. 7. Extra Slides
  8. 8. Extra Slide 1 - Dataset Product Name Product Category - - Average Retail Price Minimum Sale Price Offer Price Offer Status Lenses Photography - - $1500 $1200 $1150 Accepted Guitar Music - - $625 $600 $400 Disregarded Percentage of Accepted Offers Musical Instruments Appliances Photography TV & Home Theater Countered vs Non-countered Offers - Provided dataset: ~13,000 rows (offers history) for ~1000 products - Greentoe wanted to include subcategories and brands - Greentoe wanted to incorporate information from counter offers Musical Instruments Appliances Photography TV & Home Theater
  9. 9. Extra Slide 2 – Input Screenshot
  10. 10. Extra Slide 3 – Output 1 Screenshot
  11. 11. Extra Slide 4 – Output 2 Screenshot

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