In this repository, a regression model is built and validated using the data provided.
The dataset is provided in a data.csv file and includes multiple variables. The task is to build a regression model that explains the dependent variable using the other variables in the dataset.
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Model Selection and Validation:
- Build a regression model using the dependent variable and the other variables in the dataset.
- Choose the model algorithm, and you can test multiple algorithms (optional).
- Decide which variable(s) to use for splitting the data into training and validation samples.
- Justify your chosen validation approach.
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Regression Results:
- Present the regression results using a scatter plot.
- Use aesthetics to indicate different groups on the plot. You may need separate scatter plots for different groups (depending on the case).
- Approach Justification: Description and justification of approach is presented in a Jupyter-Notebook report.
- Include Plot: The report includes the scatter plot visualization.