regression

How to Build a Regression Model in Catalysis?

Building a regression model in catalysis involves several steps:
1. Data Collection: Gather data on catalytic activity and various influencing factors.
2. Data Preprocessing: Clean the data to remove any inconsistencies or outliers.
3. Model Selection: Choose the appropriate regression model (linear, multiple, non-linear) based on the nature of the data.
4. Model Training: Use a portion of the data to train the model.
5. Model Validation: Validate the model using the remaining data to ensure its accuracy.
6. Optimization: Fine-tune the model parameters to improve performance.

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