Implement from scratch the ridge regression algorithm for regression with square loss. Apply the algorithm to the prediction of the label medianHouseValue in this dataset. Study the dependence of the cross-validated risk estimate on the parameter alpha of ridge regression. Try using PCA to improve the risk estimate. Optionally, use nested cross-validated risk estimates to remove the need of choosing the parameter.
Here is a description of the attributes in the dataset:
- longitude: A measure of how far west a house is; a higher value is farther west
- latitude: A measure of how far north a house is; a higher value is farther north
- housingMedianAge: Median age of a house within a block; a lower number is a newer building
- totalRooms: Total number of rooms within a block
- totalBedrooms: Total number of bedrooms within a block
- population: Total number of people residing within a block
- households: Total number of households, a group of people residing within a home unit, for a block
- medianIncome: Median income for households within a block of houses (measured in tens of thousands of US Dollars)
- medianHouseValue: Median house value for households within a block (measured in US Dollars)
- oceanProximity: Location of the house w.r.t ocean/sea
Note: The dataset has an attribute with missing values and an attribute with categorical values. Find a way of handling these anomalies and justify your choice.
Copyright 2020 (c) Anna Olena Zhab'yak, Michele Maione. All rights reserved.
Licensed under the MIT License.