Predictive analytics
- 1. ?????? ?????? 1 ?????? ????????? ????????? ?????? PREDICTIVE ANALYTICS "????????????? ??????? ????? ?????,??????? ??????? ????????" )?????? ??????( ?????? ?????? wiesel@idc.ac.il 062-3881855 1 The Power to Predict Who Will Click, Buy, Lie, or Die ??????????????-???????????????? ???????? ????????? ???? ??????? ????????, ???? ?????? ???? ?????? ?????? ?????"?????? ???????"? ????????: ?????????? ???? ??????? ?????? ???? ?????? ?????? ?????? ?????????? ??????? ??????????? ?????? ???? ?????? ?????? ?????? ???????? ??????? ???????? ??????? ???? ?????? ?????? ?????? ??????? ?????? ?????? ?????? ?????? ?????? ?????? ?????? ?????? 2
- 2. ?????? ?????? 2 ?????? ????????? ????????? ?????? ????????????????? ? 1. Identifying people who don¨t pay their taxes. ? 2. Calculating the probability of having a stroke in the next 10 years. ? 3. Spotting which credit card transactions are fraudulent. ? 4. Selecting suspects in criminal cases. ? 5. Deciding which candidate to offer a job to. ? 6. Predicting how likely it is that a customer will become bankrupt. ? 7. Establishing which customers are likely to defect to a rival phone plan ? when their current contract is up. ? 8. Producing lists of people who would enjoy going on a date with you. ? 9. Determining what books, music and films you are likely to purchase next. ? 10. Predicting how much you are likely to spend at your local supermarket ? next week. ? 11. Forecasting life expectancy. ? 12. Estimating how much someone will spend on their credit card this year. ? 13. Inferring when someone is likely to be at home (so best time to call them). 3 ???????? ?????????C????????? ?????? )???????,????????,???????( 4 ???? ?????????? ????? ?????? ???????: ???????? ?????? ????? ????????? ????? ??????? ??????? ??????? ?????? ??????? ???????? ???????? ????? ???????? ????? ????? ?????'???????? ???????? ???????...
- 3. ?????? ?????? 3 ?????? ????????? ????????? ?????? Airbnb and Big data: ＾Price Tips￣ 5 ? Price Tips is a guide that tells hosts, for each day of the year, how likely it is for them to get a booking at their current price. ? Hosts can see what dates are likely to be booked at their current price (green) and which aren¨t (red). ? When price is within 5% of the suggested price, the chances are nearly four times to get a booking. Linear Model ????????:????????? ???????? ????? ????? ??????? 6
- 4. ?????? ?????? 4 ?????? ????????? ????????? ?????? Credit scoring ??????? ???????????"???????" ?????? ????8????????? 7 ????????? ???????-???????????????? ????? ????????? ?????? 8
- 5. ?????? ?????? 5 ?????? ????????? ????????? ?????? ???????????????????? 9 ???????? ??????: ?????????? ???????? ????? ???????C500$ ???????? ???????? ????? ???????C8,000$ ?????? ???????? ?????? ??????1:16 ???????? ??????? ???? ???????? ?????????<580 Regression Model 10 ???????: ?????? ??????25,000??????? ??????? ???????? ?????????: ?$1.2???????? ???????: ?????? ?????? ???????? ??????75$ ?????? ?????? ???????? ??????2$ ???????: ????? ??????? ???? ???????? ????????5.1???????? ??????? ?????? ???? ???????? ????????,?????, ???????,?????? ????? ???? ??????? ??????C?????? ????? ??????? ???? ?????? ?????
- 6. ?????? ?????? 6 ?????? ????????? ????????? ?????? 11 ????????? ??????: ????? ????????600,000???????)1.2$????????( ???????predictive: ????? ????????100,000???????)200,000$( ????????? ?????? ?????? ???????? ???????? Predictive Analytics 12 ?Predictor variable: ???????? ???????? ?????? ?????? ???? ??????? ?... ?Behavioral data: ????? ???? ????? ??????
- 7. ?????? ?????? 7 ?????? ????????? ????????? ?????? ??????100,000???????????1,600????? 13 ??????????????C??????????? 14
- 8. ?????? ?????? 8 ?????? ????????? ????????? ?????? ???????????????? 15 ???????????????3?????????9-11 16
- 9. ?????? ?????? 9 ?????? ????????? ????????? ?????? ??????????????C??????????? 17 ???????? 18 ???????: ????? ?????? ??????500,000$
- 10. ?????? ?????? 10 ?????? ????????? ????????? ?????? Regression Model 19 ?????? ???????? ???????75$ ???? ???????3?????? ????????: ???????????????????1-8 20