Modeling and Evaluation: Explain Prediction and Classification using Simple Linear Regression y = mx + c

Many people explain prediction, classification using many formulas. The author will try to explain prediction using simple Linear Regression, y=mx + c, which you learn in high school and secondary schools. For Data Mining process, we usually use CRISP DM data mining process:

Extracted from: https://www.datascience-pm.com/crisp-dm-2/

Data Mining process steps includes Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment.

- Business Understanding step - we need to understand the business and establish the question we need to answer for the data mining

- Data Understanding step - we need to understand the data. We can use statistics such as descriptive, regression analysis to understand the data.

- Data Preparation step - it is the cleaning of the data and we can remove duplicates here.

- Modeling step - we create clustering models, prediction models, classification models.

- Evaluation step - we evaluate which models is more accurate and select.

- Deployment steps - we can create data products.



For Data Science, at the Deployment steps, we create data products for businesses. We can create softwares that predicts…