Week – 4 Graded quiz How to Win a Data Science Competition Learn from Top Kagglers
1. Which hyperparameters are first to tune in sklearn’s RandomForest?
2. Suppose you fit LightGBM to your train data and check performance on the validation set. The train set consists of 500 rows and 1000 different features and validation set consist of 50 objects. You run automatic hyperparameter optimization method overnight and in the morning you select the best parameters, produce results for the test set and submit to the leaderboard. We also know that test set comes from the same distribution as train and validation sets.
3. Suppose you want to find a good set of hyperparameters for a dataset with 1000 points and have resources to do fitting 2000 times. Which method of model selection your should use?
4. Suppose you train Neural Network with SGD and see that it overfits data. Which of the following actions can help you to regularize model?