10 Questions
What is the Cross Industry Standard Process for Data Mining?
A step-by-step process for data mining
What is an important part of understanding the objective of the problem?
Prior knowledge
What is an important part of data preparation?
Data quality checks
What is a necessary step for creating a model?
Model building
What is a necessary step for evaluating a model?
Creating test data
What is an important part of the CRISP DM process?
Knowledge and actions
What is an example of knowledge and actions that is important for continuing the CRISP DM process?
All of the above
What is an important part of data preparation?
Data exploration
What is a necessary step for creating a model?
Model building
What is an important part of the CRISP DM process?
Knowledge and actions
Study Notes
- The Cross Industry Standard Process for Data Mining, or CRISP DM, is a step-by-step process for data mining.
- Prior knowledge is important for understanding the objective of the problem, the subject area of the problem, and the data.
- Data must be prepared before modeling can be done. This includes data exploration, data quality checks, handling missing values, data type conversion, transformation, and outliers.
- Model building and evaluation is done using algorithms.
- Test data must be created and used to evaluate the model.
- The CRISP DM process is repeated for different types of data.
- Knowledge and actions are important for continuing the CRISP DM process after the model is built. This includes training data, testing the model, and applying the model to new data.
Test your knowledge of the CRISP DM data mining process with this quiz. Explore the steps involved in preparing data, building and evaluating models, and repeating the process for different data types.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
