Practicing Machine Learning Interview Questions in Python
Lisa Stuart
Data Scientist
parameter | Random Forest | Gradient Boosting |
---|---|---|
n_estimators |
10 |
100 |
criterion |
gini (or entropy ) |
friedman_mse |
max_depth |
None |
3 |
learning_rate |
N/A | 0.1 |
Function | returns |
---|---|
sklearn.ensemble.RandomForestClassifier |
Random Forest |
sklearn.ensemble.GradientBoostingClassifier |
Gradient Boosted Model |
sklearn.metrics.accuracy_score |
trained model accuracy |
sklearn.metrics.confusion_matrix(y_test,y_pred) |
confusion matrix |
sklearn.metrics.precision_score(y_test,y_pred) |
precision |
sklearn.metrics.recall_score(y_test,y_pred) |
recall |
sklearn.metrics.f1_score(y_test,y_pred) |
f1 score |
Practicing Machine Learning Interview Questions in Python