The document discusses linear regression and demonstrates its use through three machine learning demos. It begins with an introduction to linear regression, the Weka software, and a first demo using Weka's GUI. It then describes the microservices architecture of a second demo using Weka's Java API with Spring Boot microservices. Finally, it outlines a third full stack demo built with Angular 10. Source code for the demos is available online.

1. Linear Regression
Microservices with Spring Boot and Spring Cloud
Full Stack app with Angular 10
Marco Yuri Fujii Melo

2. 2
Agenda

Quick introduction to Linear Regression

Weka Machine Learning Software

Demo #1 using Weka GUI

Microservices Architecture of Demo #2

Demo #2 with three Microservices, using Weka Java API
➔ Spring Data JPA using H2 database
➔ Centralized Configuration with Spring Cloud Config Server and Git repository
➔ Service Invocation using Feign
➔ Load Balancing with Ribbon
➔ Eureka Naming Server
➔ API Gateway with Zuul
➔ Distributed Tracing with Zipkin, Sleuth and RabbitMQ
➔ Broadcast of configuration changes with Spring Cloud Bus and RabbitMQ
➔ Fault Tolerance with Hystrix

Demo #3 – Full Stack Application with Angular 10

3. 3
Linear Regression - Definition
“Linear regression is a way to explain the
relationship between a dependent variable and
one or more explanatory variables using a
straight line.”
(Wikipedia)

4. 4
Linear Regression - Equation
γ = α + β1x1 + β2x2 + … + βnxn + ε
γ - the dependent variable (the value to be predicted)
α - the intercept (the value of γ when x = 0)
β - the slope of the line (a.k.a. regression coefficient)
x - the independent variable (a.k.a. explanatory variable)
ε - the error term (a.k.a. residual), reflects the unexplained
variation in γ

5. 5
Linear Regression - Graph

The blue points are actual samples.

With linear regression all points can be connected using a single, straight line.

6. 6
Weka
(Waikato Environment for Knowledge Analysis)

Weka is an open source machine learning
software that can be accessed through a GUI,
standard terminal applications, or a Java API

Developed at the University of Waikato, New
Zealand

Licensed under the GNU General Public License

Available at:
https://www.cs.waikato.ac.nz/ml/weka/

7. 7
Weka - GUI

8. 8
Weka – ARFF File

ARFF (Attribute-Relation File Format) file is an
ASCII text file that describes a list of instances
sharing a set of attributes

ARFF files were developed by the Machine
Learning Project at the Department of Computer
Science of The University of Waikato for use with
the Weka machine learning software

The ARFF file format is:
@relation <relation-name>
@attribute <attribute-name> <datatype>
@data

9. 9
ARFF File for Weka GUI Demo
@RELATION house
@ATTRIBUTE houseSize NUMERIC
@ATTRIBUTE lotSize NUMERIC
@ATTRIBUTE bedrooms NUMERIC
@ATTRIBUTE granite NUMERIC
@ATTRIBUTE upgradedBathroom NUMERIC
@ATTRIBUTE sellingPrice NUMERIC
@DATA
3529,9191,6,0,0,205000
3247,10061,5,1,1,224900
4032,10150,5,0,1,197900
2397,14156,4,1,0,189900
2200,9600,4,0,1,195000
3536,19994,6,1,1,325000
2983,9365,5,0,1,230000

10. 10
Weka – Demo #1
Demo #1 using Weka GUI

11. 11
Weka Explorer
Loading ARFF data file into Weka.

12. 12
Weka with data loaded

13. 13
Choosing LinearRegression model
Click on Classify tab, then Choose > functions > LinearRegression.
In Test options, select Use training set and sellingPrice, then hit Start.

14. 14
Regression output

15. 15
Linear Regression Model
sellingPrice =
-26.6882 * houseSize +
7.0551 * lotSize +
43166.0767 * bedrooms +
42292.0901 * upgradedBathroom +
-21661.1208
The regression model tells that granite in the
kitchen doesn’t affect the house’s value.

16. 16
Applying the regression model equation
sellingPrice =
-26.6882 * 3198 +
7.0551 * 9669 +
43166.0767 * 5 +
42292.0901 * 1 +
-21661.1208
sellingPrice = 219,328

17. 17
Microservices Architecture of Demo #2

18. 18
Microservices Architecture of Demo #2

19. 19
Microservices Architecture of Demo #2

20. 20
Microservices Architecture of Demo #2

21. 21
Demo #2 – H2 Database

22. 22
Demo #2 – Eureka Naming Server

23. 23
Demo #2 - Postman

24. 24
Demo #2 – Zipkin Distributed Tracing

25. 25
Weka – Demo #2
Demo #2 using Microservices and Weka Java API
Source code is available at: https://github.com/marcoyf

26. 26
Demo #3 – Angular 10 web app

27. 27
Demo #3 – Angular 10 web app

28. 28
Weka – Demo #3
Demo #3 – Full Stack app with Angular 10
Source code is available at: https://github.com/marcoyf

29. 29
Thank you

30. 30
References

https://developer.ibm.com/technologies/analytics/articles/os-weka1/

https://simple.wikipedia.org/wiki/Linear_regression

https://www.cs.waikato.ac.nz/ml/weka/