Home Construction Cost Estimation Using ML

@article{1704488,
      author = {Suchetha N V, Adithya, Ashik S, Dhanush, ThrineshReddy S Guledagudda},
      title = {Home Construction Cost Estimation Using ML},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {11},
      pages = {536-543},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704488.pdf},
      abstract = {Machine learning has played a significant role in diverse fields, including speech recognition, product recommendations, and the medical industry. Its application has led to advancements in customer service and automobile safety, making it a widely adopted technology across various domains. With the constant fluctuations in housing prices, individuals are seeking to purchase new homes within their budget while analyzing market trends. However, the existing systems for predicting home costs suffer from a notable drawback as they do not consider future market trends, potentially leading to unexpected price increases. In light of this, our project aims to address this issue by developing a housing cost prediction model that eliminates losses and provides accurate estimations. To achieve this, we are utilizing several machine learning algorithms, namely Linear Regression, Gradient Boost Regression, and XGBoost Regression. By incorporating these algorithms, we aim to enable individuals to make informed property investments without the need for a broker. Through our research, we have determined that the Linear Regression algorithm yields the highest accuracy in predicting home costs.},
      keywords = {Terms accuracy, house cost, Housing prices, Machine Learning},
      month = {May},
  }