Comments (3)
SameerMahajan-GSLab
commented on August 25, 2024
@levithatcher @taylorlarsen and @mmastand do you have any input on this? Otherwise we will submit a PR for its fix soon.
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mmastand
commented on August 25, 2024
We have had good luck using the following in our other work:
- Numeric:
- Mean
- Bagged trees imputation
- Assign to an outlying number such as
-999and then use a tree-based method.
- Categorical:
- New category,
missing - Bagged trees
- New category,
What do you think about these methods? We'd be grateful if you wanted to do a PR!
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vijayphugat
commented on August 25, 2024
I want to do PR on this finding and currently I am using below techniques:
- For Numeric variable : RandomForestRegressor
- For Categorical variable : RandomForestClassifier
Both of these methods work good on linear as well as non-linear type of data.
from healthcareai-py.
Related Issues (20)
- Regression metric predicting the mean
- When instantiating trainer guess which label is positive class for binary classifications HOT 1
- Pass all params through to sklearn
- Method for changing a Y/N column to 1/0 should be made generic
- Trained random forest models should have a .plot_feature_importances() method
- Random forest feature importance plot should be rotated so labels are readable
- random forest feature importance plot should have fixed height bars and scale the plot as n increases
- Models trained with no grain column fail on making predictions HOT 2
- Turn off top factors HOT 2
- Allow custom Scikit params to be passed through in the advanced class HOT 3
- Error in verification HOT 1
- Utilities :: Stratified Sampling HOT 1
- Utilities :: Validation Prediction Distribution Plots
- resolve merge conflict with 449/467
- Prediction fails if no grain column existed on training HOT 1
- confusion matrix plot should accept an optional cutoff argument HOT 1
- module 'pandas.core.common' has no attribute 'is_categorical_dtype' error HOT 4
- Methods to implement dimension reduction techniques.
- Error after installing healthcareai on ubuntu (Pyhton 3.8)
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