1.What is the name of the function that takes the input and maps it to the output variable called?
- Map Function
- None of the options
- Hypothesis Function
- Model Function
- Answer: 3)Hypothesis Function
2.What is the process of dividing each feature by its range called?
- Feature Scaling
- None of the options
- Feature Dividing
- Range Dividing
Answer: 1)Feature Scaling
3.Problems that predict real values outputs are called __________
- Classification Problems
- Regression Problems
- Real Valued Problems
- Greedy Problems
Answer: 2)Regression Problems
4.The result of scaling is a variable in the range of [1 , 10].
- False
- True
Answer: 1)False
5.The objective function for linear regression is also known as Cost Function.
- False
- True
Answer: 2)True
6.What is the Learning Technique in which the right answer is given for each example in the data called?
- Unsupervised Learning
- Supervised Learning
- Reinforcement Learning
- Right Answer Learning
Answer: 2)Supervised Learning
7.Output variables are also known as feature variables.
- False
- True
Answer: 1)False
8.Input variables are also known as feature variables.
- False
- True
Answer: 2)True
9.____________ controls the magnitude of a step taken during Gradient Descent.
- Parameter
- Step Rate
- Momentum
- Learning Rate
Answer: 4)Learning Rate
10.Cost function in linear regression is also called squared error function.
- False
- True
Answer: 2)True
11.For different parameters of the hypothesis function, we get the same hypothesis function.
- False
- True
Answer: 1)False
12.How are the parameters updated during Gradient Descent process?
- Sequentially
- Simultaneously
- Not updated
- One at a time
Answer: 2)Simultaneously
Quiz on Gradient Descent
1.For ____________, the error is determined by getting the proportion of values misclassified by the model.
- Classification
- Clustering
- None of the options
- Regression
Answer: 1)Classification
2.High values of threshold are good for the classification problem.
- True
- False
Answer: 2)False
3.Underfit data has a high variance.
- True
- False
Answer: 2)False
4.____________ function is used as a mapping function for classification problems.
- Linear
- Sigmoid
- Convex
- Concave
Answer: 2)Sigmoid
5.Classification problems with just two classes are called Binary classification problems.
- True
- False
Answer: 1)True
6.Where does the sigmoid function asymptote?
- -1 and +1
- 0 and 1
- -inf and +inf
- 0 and inf
Answer: 2)0 and 1
7.Lower Decision boundary leads to False Positives during classification.
- False
- True
Answer: 2)True
8.Linear Regression is an optimal function that can be used for classification problems.
- False
- True
Answer: 1)False
9.For ____________, the error is calculated by finding the sum of squared distance between actual and predicted values.
- Regression
- None of the options
- Classification
- Clustering
Answer: 1)Regression
10.I have a scenario where my hypothesis fits my training set well but fails to generalize for the test set. What is this scenario called?
- Underfitting
- Generalization Failure
- Overfitting
- None of the options
Answer: 3)Overfitting
11.What is the range of the output values for a sigmoid function?
- [0,.5]
- [-inf,+ inf]
- [0,1]
- [0,inf]
Answer: 3)[0,1]
12.____________ is the line that separates y = 0 and y = 1 in a logistic function.
- Divider
- None of the options
- Separator
- Decision Boundary
Answer: 4)Decision Boundary
13.Reducing the number of features can reduce overfitting.
- False
- True
Answer: 2)True
14.A suggested approach for evaluating the hypothesis is to split the data into training and test set.
- True
- False
Answer: 1)True
15.Overfitting and Underfitting are applicable only to linear regression problems.
- True
- False
Answer: 2)False
16.Overfit data has high bias.
- False
- True
Answer: 1)False
ML Exploring the Model - Final Quiz
1.For an underfit data set, the training and the cross-validation error will be high.
- True
- False
Answer: 1)True
2.For an overfit data set, the cross-validation error will be much bigger than the training error.
- True
- False
Answer: 1)True
3.Problems, where discrete-valued outputs are predicted, are called?
- Real Valued Problems
- Classification Problems
- Greedy Problems
- Regression Problems
Answer: 2)Classification Problems
4.What measures the extent to which the predictions change between various realizations of the model?
- Deviation
- Bias
- Variance
- Difference
Answer: 3)Variance
