I am using RandomForestClassifier
from scikit-learn
and I get the following results:
- "accuracy of 77%" with a train/test split 75/25%.
- "accuracy of about 76%" with cross-validation (
cv=5
) using the entire sample.
I am happy so far...
However, what do I do now? I want a final shippable model to pickle and use it on data, give it to a friend and say "this is the best I could do...". So,
- Do I train on all X,y? and
joblib.dump(clf, 'final_shippable_supermodel.pkl')
- Do I train on using
X_train
,y_train
from a random split?
ALSO, note that I understand 77% might not meet the standards of those who answer. I am just trying to understand the steps. An, yes, I have good precision and recall scores.