real_estate_valuation: Real Estate Valuation Dataset A dataset containing features...

In TFM: Sparse Online Principal Component for Truncated Factor Model

Real Estate Valuation Dataset A dataset containing features related to residential property valuation in New Taipei City, Taiwan, including house age, proximity to transit (MRT), local amenities (convenience stores), geographic coordinates, and the target valuation.

Description

Real Estate Valuation Dataset

A dataset containing features related to residential property valuation in New Taipei City, Taiwan, including house age, proximity to transit (MRT), local amenities (convenience stores), geographic coordinates, and the target valuation.

Usage

real_estate_valuation

Format

A data frame with 414 observations (rows) and 6 variables:

X1 house age

House age (years). Older properties typically experience depreciation, which influences valuation.

X2 distance to the nearest MRT station

Distance to the nearest MRT (Mass Rapid Transit) station (meters). Closer transit access generally increases property value.

X3 number of convenience stores

Number of nearby convenience stores. More amenities correlate with higher desirability and valuation.

X4 latitude

Latitude (decimal degrees). Geographic coordinate for spatial analysis of location-based value trends.

X5 longitude

Longitude (decimal degrees). Geographic coordinate for spatial analysis of location-based value trends.

Y

Real estate valuation (10,000 New Taiwan Dollars per ping). The target variable representing property value. (Note: 1 ping = 3.3058 m², a local unit of area in Taiwan.)

TFM documentation built on June 9, 2025, 9:08 a.m.