What is the primary risk of not performing a train-test split in a machine learning workflow?
The training time will increase.
The model might overfit the training data and perform poorly on new data.
The dataset may become unbalanced.
The model may fail to converge.
Why is data preprocessing necessary before using it for model building?
The data may contain outliers or missing values due to errors in data collection.
Features may have different scales, affecting model performance.
The dataset may include non-numerical features that need to be converted to numerical representations.
All of these
What is the purpose of the tol parameter in the fit method of the stochastic regressor?
from sklearn.linear_model import SGDRegressorfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import mean_squared_errorfrom sklearn.datasets import load_breast_cancer
X,y = load_breast_cancer(return_X_y=True)
model = SGDRegressor(early_stopping=True, validation_fraction=0.2, tol=0.001, n_iter_no_change=5)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
model.fit(X_train, y_train)y_pred = model.predict(X_test)mse = mean_squared_error(y_test, y_pred)It specifies the tolerance level for early stopping based on the change in the validation error.
It controls the learning rate of the stochastic regressor during training.
It determines the maximum number of iterations for the training process.
It defines the fraction of the validation set used for early stopping.
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The IIT Madras BS Machine Learning Practice (MLP) Quiz 1 paper sat on 23 Feb 2025, in the January 2025 term: 20 questions for 40 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.
| Feature | MLP Quiz 1 23 Feb 2025 at a glance |
|---|---|
| Term | January 2025 term |
| Subject | Machine Learning Practice |
| Course code | BSCS2008 |
| Questions | 20 |
| Marks | 40 |
| Duration | 120 min |
| MCQ | 11 |
| MSQ | 4 |
| Numerical | 5 |
| Official paper | IIT M DIPLOMA AN EXAM QDD2 23 Feb 2025 |
| Negative marking | No negative marking. |
| Updated |