We aim to build predictive models for Airbnb’s prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.
|Number of pages||7|
|Journal||Journal of Information and Communication Convergence Engineering|
|Publication status||Published - 2022|
Bibliographical noteFunding Information:
Dr. Woo received his Ph.D. from USC and w ent to Yonsei University. He is a Professor at CIS Department of California State University Los Angeles and serves as a Technical Advisor of Teradata, Spark Technology Center and KSEA-SC. He has consulted companies in Hollyw ood. He has published more than 50 papers regarding Scalable Deep Learning, Big Data Analysis and Prediction. He has been awarded Teradata TUN faculty Scholarship and received grants from Databricks, NVidia, Amazon, IBM, Oracle, Microsoft, Cloudera, Hortonworks, SAS, QlikView, and Tableau.
The Databrick University Alliance supported this research. We appreciate the support of Rob Reed, Program Director at Databricks University Alliance
© The Korea Institute of Information and Communication Engineering
All Science Journal Classification (ASJC) codes
- Information Systems
- Media Technology
- Computer Networks and Communications
- Electrical and Electronic Engineering