Normalize training data

[nya-elimu]

https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html

Why?
Why normalize the training data? To check if that would improve the accuracy score.

[howdyDp]

I was trying to normalize the data, i wanted to know what kind of normalization are you looking for ?
min max normalization or z-scaled normalization and this is my first open source contribution so if you have any advice do let me know

[jo-elimu]

@howdyDp We are looking for whichever normalization technique would result in an improved accuracy score.

Tip

Try running python run_all_steps.py for each kind of normalization you want to try, and see if that results in improvements in step3_2_accuracy_score.txt and step3_2_mean_absolute_error.txt

And if it turns out that normalization does not improve the accuracy, then we wouldn't use normalization at all.

[eve-b612]

Hi! I see the issue is still open, so I thought I would give this a try. This is my first contribution, I've normalised the data 3 ways and wanted to share the results. My work is in a jupyter notebook, I've forked the repo and created a new branch named 'normalisation-experiment'. I wanted to know which folder to upload this in the repo branch?

[jo-elimu]

@eve-b612 Feel free to open a pull request 🙂

You can add your code changes related to data processing to the step1_prepare folder.

[eve-b612]

Sent the pull request for review! :)