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7/25/2019 Kaggle - Springleaf Data
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Kaggle Springleaf DataProposition Data
Springleaf Marketing Response
https://www.kaggle.com/c/springleaf-marketing-response/details/timeline
https://www.kaggle.com/c/springleaf-marketing-response/details/timelinehttps://www.kaggle.com/c/springleaf-marketing-response/details/timeline7/25/2019 Kaggle - Springleaf Data
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HomeDetermine whether to send a direct mail piece to a cstomer
Springleafpts the hmanit! "ack into lending "! o#ering their cstomerspersonal and ato loans that help them take control of their li$es and their
%nances. Direct mail is one important wa! Springleaf&s team can connect with
cstomers whom ma! "e in need of a loan.
Direct o#ers pro$ide hge $ale to cstomers who need them' and are a
fndamental part of Springleaf&s marketing strateg!. (n order to impro$e their
targeted e#orts' Springleaf mst "e sre the! are focsing on the cstomers
who are likel! to respond and "e good candidates for their ser$ices.
)sing a large set of anon!mi*ed featres' Springleaf is asking !o to predict
which cstomers will respond to a direct mail o#er. +o are challenged to
constrct new meta-$aria"les and emplo! featre-selection methods to
approach this dantingl! wide dataset.
https://www.springleaf.com/https://www.springleaf.com/7/25/2019 Kaggle - Springleaf Data
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Data
Data ,iles
See this eample R Script that trains an 0oost model and creates a
s"mission+o are pro$ided a high-dimensional dataset of anon!mi*ed cstomer
information. 1ach row corresponds to one cstomer. 2he response $aria"le
is "inar! and la"eled 3target3. +o mst predict the target $aria"le for e$er!
row in the test set.
2he featres ha$e "een anon!mi*ed to protect pri$ac! and are comprised of a
mi of continos and categorical featres. +o will enconter man!
3placeholder3 $ales in the data' which represent cases sch as missing $ales.
4e ha$e intentionall! preser$ed their encoding to match with internal s!stems
at Springleaf. 2he meaning of the featres' their $ales' and their t!pes are
pro$ided 3as-is3 for this competition5 handling a hge nm"er of mess!featres is part of the challenge here.
https://www.kaggle.com/benhamner/springleaf-marketing-response/xgboost-examplehttps://www.kaggle.com/benhamner/springleaf-marketing-response/xgboost-examplehttps://www.kaggle.com/benhamner/springleaf-marketing-response/xgboost-examplehttps://www.kaggle.com/benhamner/springleaf-marketing-response/xgboost-example7/25/2019 Kaggle - Springleaf Data
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(nformation1$alationS"missions are e$alated on area nder the R67 cr$e"etween the predicted
pro"a"ilit! and the o"ser$ed target.
S"mission ,ile,or each (D in the test set' !o shold predict a pro"a"ilit!. 2he %le shold
contain a header and ha$e the following format:
http://en.wikipedia.org/wiki/Receiver_operating_characteristichttp://en.wikipedia.org/wiki/Receiver_operating_characteristic