- Suppose the following historic data is available that can be used to predict the price at which a house would sell in city A.
| Sq.ft in 100s | Rooms | House Price in 100,000s |
| 5 | 2 | 1.4 |
| 6 | 3 | 2 |
| 7.5 | 3 | 2.5 |
| 9 | 4 | 3.5 |
| 10 | 4 | 4 |
| 11 | 5 | 5 |
- [1 pt] How many samples are in the house price dataset shown above?
- [3 pts] How many features are shown for this dataset? What are the features for this dataset?
- [5 pts] Use all the features to initialize a linear regression model for this dataset with all the weights set as the same value. Write the equation of the model.
- [5 pts] Create a polynomial regression model for this dataset with all the weights initialized with random values. Write the equation that represents your model. For this question, you may use all the features or a subset of the features.
- Suppose the following historic data is available to predict Y given X1 and X2.
- [6 pts] Fill the predicted Y and the difference between predicted and actual for the regression model given by Y = 0.14×1+ 0.14 x22.
- [10 pts] What is the least mean square error (LMSE) for the dataset. Show all calculations
- [10 pts] Show one iteration of training the regression model using gradient descent on the least mean square error (LMSE).
| x1 | x2 | Y | Predicted Y | Actual – Predicted |
| 3 | 2 | 1 | ||
| 5 | 3 | 2 | ||
| 6 | 3 | 2.2 | ||
| 7 | 4 | 3.2 | ||
| 8 | 4 | 3.4 | ||
| 10 | 5 | 5 |
- Suppose the following historic data is available that can be used to predict if someone would repay their loan.
The post How many samples are in the house price dataset shown above? [3 pts] How many features are shown for this dataset? What are the features for this dataset? [5 pts] Use all the feature appeared first on My Academic Papers.
