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Hi Kathan, this is very comprehensive.
Will go over design choices in a meeting, but just so you can get an idea of what I'm thinking so far. Unfortunately this is too large in it's current state for me to actually get through.
I've only reached up to the dataloader part of the training script.
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Fairly certain you can remove this.
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Fairly certain you can also remove this.
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You can definitely remove this.
| test_size: Proportion of data for testing | ||
| stratify: Whether to use stratified splitting | ||
| random_state: Random state for reproducibility | ||
| feature_engineering: Whether to perform automated feature engineering |
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Good that you included the args here!
| self.stratify = stratify | ||
| self.random_state = random_state | ||
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| # Initialize DataLoader |
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At this point can you find and replace all "Initialize" with "Initialise" please
| self.random_state = random_state | ||
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| # Initialize DataLoader | ||
| self.data_loader = DataLoader( |
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This is very different to our other projects, I think this is in place of the data importer we use elsewhere?
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| # Import utility modules | ||
| from .utils.data_utils import FeatureEngineer, FeatureSelector, DataTransformer, DataProfiler | ||
| from .utils.visualise import DataVisualizer |
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| class DataLoader: | ||
| """ | ||
| Enhanced class to load, clean, visualize and prepare data for machine learning. |
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"Enhanced" from what?
This docstring is quite vague.
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Linked Issue(s)
Summary of changes
Added the structured data template with a stand alone file for data exploration on the exisitng template V2
Reason for changes
Enhancement