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Kaggle Competition Prudential Life Insurance Assessment

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Presentation on theme: "Kaggle Competition Prudential Life Insurance Assessment"— Presentation transcript:

1 Kaggle Competition Prudential Life Insurance Assessment
Can you make buying life insurance easier? Advanced Network Database Lab

2 Registration Site: https://www.kaggle.com/competitions
Account: IKDD1(Group Number)

3 Prudential Prudential Financial, Inc.
An American Fortune Global 500 and Fortune 500 company $ 30,000

4 Prudential Competition url: Data url: /data Leaderboard: /leaderboard

5 Data Attribute

6 Data Attribute Nominal type
Numbers may be used to represent the variables but the numbers do not have numerical value or relationship.

7 Classification

8 Prediction

9 Decision Tree

10 Sklearn – Python tool Simple and efficient tools for data mining and data analysis! Decision tree url :

11 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)

12 Homework 2 Improve your prediction results Oral report
Deadline: next Thursday (1/7)

13 Homework 3 (Final project)
Try different algorithms to build the best classifier Submit the result to Kaggle

14 Final project Deadline: 1/14 23:59 Submission:
Submit the results to kaggle your project to Project file content: code prediction result report

15 Report The details of the your best method
The description of the methods that you tried The important attributes or surprised features you found

16 Grading Homework 1: 20% Homework 2: 10% Final Project : 70%
The ranking: 20% Algorithm and coding : 25% Report: 25%

17 XGBoost General purpose gradient boosting library, including generalized linear model and gradient boosted decision tree SITE:

18 tslm A linear model with time series components
SITE:

19 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:


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