Skip to main content

Machine Learning: Regression MethodsLaajuus (5 cr)

Code: TT00CE02

Credits

5 op

Teaching language

  • Finnish
  • English

Responsible person

  • Juha Peltomäki
  • Mika Rantonen

Objective

Regression models can be used to predict numerical values for new observations. You get to know different regression methods and know how to compare their results and analyze the performance of the model. You also familiarize yourself with the methods of calculating error terms in regression analysis.

EUR-ACE Knowledge and Understanding
You understand different regression methods and how to apply these to business problems.

EUR-ACE Engineering practice
You know how to use and apply different regression methods. You know how to use different regression models, and you know how to compare their results and analyze the performance of the model. You know the most common methods of calculating error terms in regression analysis.

Content

Basic concepts of regression analysis
Overview of regression methods
Linear regression
Nonlinear regression
Logistic regression
Random Forest regression method
Interpretation of regression analysis results
Assessment of model accuracy

Qualifications

Basics of Programming

Assessment criteria, satisfactory (1)

Sufficient (1)
You know some regression methods. You can use simple regression models. You know some way of calculating error terms in regression analysis.

Satisfactory (2)
You know and find different regression methods. You know how to use some regression models. You know some methods of calculating error terms in regression analysis.

Assessment criteria, good (3)

Good (3)
You know how to use different regression methods. You know how to use some regression models and measure the performance of the model. You know the most common methods of calculating error terms in regression analysis.

Very good (4)
You can apply and compare different regression methods. You know how to use different regression models, and you know how to compare their results and analyze the performance of the model. You know the most common methods of calculating error terms in regression analysis and make conclusions based on the results.

Assessment criteria, excellent (5)

Excellent (5)
You can recommend and justify suitable regression methods for specific business problems. You know how to use different regression models, and you know how to interpret their results and how to interpret the performance of the model. You can explain the methods of calculating error terms in regression analysis and change the implementation based on the results.