Question

1. Implement the linear regression using the Gradient Descent
Algorithm (batch mode) using the given data splittings:
Dataset: Boston house pricing dataset.
(Hint to load the dataset
from sklearn import datasets
boston = datasets.load_boston(return_X_y=False))
a) train(30%), validation (10%), and test(60%)
The sets of hyperparameters for validation (in case of a) are
to be used :
i) Learning rate : 0.1 , rho : 0.5, epoch : 10
ii) Learning rate : 0.01, rho : 0.6, epoch : 20
iii) Learning rate : 0.02, rho : 0.7, epoch : 30
iv) Learning rate : 0.03, rho : 0.8, epoch : 40
v) Learning rate : 0.001, rho : 0.9, epoch: 50

Answer 1

Explanation:

Implement the linear regression using the Gradient Descent

Algorithm (batch mode) using the given data splittings:

Dataset: Boston house pricing dataset.

(Hint to load the dataset

from sklearn import datasets

boston = datasets.load_boston(return_X_y=False))

a) train(30%), validation (10%), and test(60%)

The sets of hyperparameters for validation (in case of a) are

to be used :