h2oai/app-consumer-loan

Name: app-consumer-loan

Owner: H2O.ai

Description: null

Created: 2015-09-28 18:01:40.0

Updated: 2017-11-03 09:31:46.0

Pushed: 2016-11-22 19:49:46.0

Homepage: null

Size: 20672

Language: HTML

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README

H2O generated POJO model WebApp Example

This example shows a generated Java POJO being called using a REST API from a JavaScript Web application.

The application simulates the experience of a consumer applying for a loan. The consumer provides some information about themselves and is either offered a loan or denied.

H2O World 2015 Presentation

The “Building a Smarter Application” presentation given at H2O World 2015 references this repo.

• https://github.com/h2oai/h2o-world-2015-training/tree/master/tutorials/building-a-smarter-application

Pieces at work

Processes

(Front-end)

1. Web browser

(Back-end)

1. Jetty servlet container

Note: Not to be confused with the H2O embedded web port (default 54321) which is also powered by Jetty.

Files

(Offline)

• build.gradle
• data/loan.csv
• script.R

(Front-end)

• src/main/webapp/index.html
• src/main/webapp/app.js

(Back-end)

• src/main/java/org/gradle/PredictServlet.java
• lib/h2o-genmodel.jar (downloaded)
• src/main/java/org/gradle/BadLoanModel.java (generated)
• src/main/java/org/gradle/InterestRateModel.java (generated)

Steps to run

Step 1: Create the gradle wrapper to get a stable version of gradle.

adle wrapper

Step 2: Install H2O's R package if you don't have it yet.

http://h2o-release.s3.amazonaws.com/h2o/rel-tibshirani/2/index.html#R

Step 3: Build the project.

gradlew build

Step 4: Deploy the .war file in a Jetty servlet container.

gradlew jettyRunWar -x generateModels

(If you don't include the -x generateModels above, you will build the models again, which is time consuming.)

Step 5: Visit the webapp in a browser.

http://localhost:8080/

Underneath the hood

Make a prediction with curl and get a JSON response.

rl "localhost:8080/predict?loan_amnt=10000&term=36+months&emp_length=5&home_ownership=RENT&annual_inc=60000&verification_status=verified&purpose=debt_consolidation&addr_state=FL&dti=3&delinq_2yrs=0&revol_util=35&total_acc=4&longest_credit_length=10"

abelIndex" : 0,
abel" : "0",
lassProbabilities" : [
0.8581645524025798,
0.14183544759742012


nterestRate" : 12.079950220424134

Notes:

• classProbabilities[1] is .1418. This is the probability of a bad loan.
• The threshold is the max-F1 calculated for the model, in this case approximately .20.
• A label of '1' means the loan is predicted bad.
• A label of '0' means the loan is not predicted bad.
• If the loan is not predicted bad, then use the interest rate prediction to suggest an offered rate to the loan applicant.

rl "localhost:8080/predict?loan_amnt=10000&term=36+months&emp_length=5&home_ownership=RENT&annual_inc=60000&verification_status=blahblah&purpose=debt_consolidation&addr_state=FL&dti=3&delinq_2yrs=0&revol_util=35&total_acc=4&longest_credit_length=10"
 HTTP error response simplified below ...]
own categorical level (verification_status,blahblah)

Performance

1. Set VERBOSE to false in src/main/java/org/gradle/PredictServlet.java

2. ./gradlew jettyRunWar -x war

3. Run apachebench as shown here:

 -k -c 8 -n 10000 "localhost:8080/predict?loan_amnt=10000&term=36+months&emp_length=5&home_ownership=RENT&annual_inc=60000&verification_status=VERIFIED+-+income&purpose=debt_consolidation&addr_state=FL&dti=3&delinq_2yrs=0&revol_util=35&total_acc=4&longest_credit_length=10"
 is ApacheBench, Version 2.3 <$Revision: 655654 $>
right 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
nsed to The Apache Software Foundation, http://www.apache.org/

hmarking localhost (be patient)
leted 1000 requests
leted 2000 requests
leted 3000 requests
leted 4000 requests
leted 5000 requests
leted 6000 requests
leted 7000 requests
leted 8000 requests
leted 9000 requests
leted 10000 requests
shed 10000 requests


er Software:        Jetty(6.1.25)
er Hostname:        localhost
er Port:            8080

ment Path:          /predict?loan_amnt=10000&term=36+months&emp_length=5&home_ownership=RENT&annual_inc=60000&verification_status=VERIFIED+-+income&purpose=debt_consolidation&addr_state=FL&dti=3&delinq_2yrs=0&revol_util=35&total_acc=4&longest_credit_length=10
ment Length:        160 bytes

urrency Level:      8
 taken for tests:   3.151 seconds
lete requests:      10000
ed requests:        0
e errors:           0
-Alive requests:    10000
l transferred:      2470247 bytes
 transferred:       1600160 bytes
ests per second:    3173.23 [#/sec] (mean)
 per request:       2.521 [ms] (mean)
 per request:       0.315 [ms] (mean, across all concurrent requests)
sfer rate:          765.49 [Kbytes/sec] received

ection Times (ms)
          min  mean[+/-sd] median   max
ect:        0    0   0.0      0       0
essing:     0    3  10.5      0      52
ing:        0    3  10.5      0      52
l:          0    3  10.5      0      52

entage of the requests served within a certain time (ms)
%      0
%      0
%      0
%      0
%      0
%      1
%     51
%     51
%     52 (longest request)

On a Macbook Pro with a 2.7 GHz Intel Core i7 this run gives:

• throughput of 3173 requests / second
• latency of 2.52 milliseconds / request

Data

The original data can be downloaded at https://www.lendingclub.com/info/download-data.action and it is all the data from 2007 to June 30, 2015. This does not incorporate the declined loan data set which does not have the same feature set. Note that some munging was done to distill the data to what is in this git repository.

References

The starting point for this example was taken from the gradle distribution. It shows how to do basic war and jetty plugin operations.

1. https://services.gradle.org/distributions/gradle-2.7-all.zip
2. unzip gradle-2.7-all
3. cd gradle-2.7/samples/webApplication/customized