advanced network database lab kaggle competition prudential life insurance assessment can you make...

Advanced Network Database Lab

Kaggle Competition

Prudential Life Insurance Assessment

Can you make buying life insurance easier?

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Registration

• Site: https://www.kaggle.com/competitions

• Account: IKDD1(Group Number)

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Prudential

• Prudential Financial, Inc.• An American Fortune Global 500 and Fortune 500 company• https://www.prulife.com.tw/page/index.htm• $ 30,000

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Prudential

• Competition url: https://www.kaggle.com/c/prudential-life-insurance-assessment

• Data url: https://www.kaggle.com/c/prudential-life-insurance-assessment /data

• Leaderboard: https://www.kaggle.com/c/prudential-life-insurance-assessment /leaderboard

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Data Attribute

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Data Attribute

• Nominal type• Numbers may be used to represent the variables but the numbers do

not have numerical value or relationship.

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Classification

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Prediction

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Decision Tree

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Sklearn – Python tool

• Simple and efficient tools for data mining and data analysis!

• Decision tree url : http://scikit-learn.org/stable/modules/tree.html

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Homework 1

• Registration

• Apply a simple algorithm to build the classifier

• To predict the "Response" variable for each Id in the test set

• Submit the result to Kaggle

• Deadline: next Thursday (12/31)

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Homework 2

• Improve your prediction results

• Oral report

• Deadline: next Thursday (1/7)

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Homework 3 (Final project)

• Try different algorithms to build the best classifier

• Submit the result to Kaggle

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Final project

• Deadline: 1/14 23:59

• Submission: • Submit the results to kaggle• Email your project to cwchang.ncku@gmail.com• Project file content:

• code • prediction result • report

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Report

• The details of the your best method

• The description of the methods that you tried

• The important attributes or surprised features you found

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Grading

• Homework 1: 20%

• Homework 2: 10%

• Final Project : 70%• The ranking: 20%• Algorithm and coding : 25%• Report: 25%

XGBoost

• General purpose gradient boosting library, including generalized linear model and gradient boosted decision tree

• SITE: http://dmlc.ml/

tslm

• A linear model with time series components

• SITE: http://www.inside-r.org/packages/cran/forecast/docs/tslm

H2o.randomForest

• Random Forest (RF) is a powerful classification tool. When given a set of data, RF generates a forest of classification trees, rather than a single classification tree. Each of these trees generates a classification for a given set of attributes. The classification from each H2O tree can be thought of as a vote; the most votes determines the classification.

• SITE: http://docs.h2o.ai/h2oclassic/datascience/rf.html