• Arvind Kumar
• Dr. Satpal

Rural data mining concerns with developing methods for discovering knowledge from Rural datasets. Data Mining is the analysis step of the KDD, a process of extracting new patterns from large data sets involving methods from statistics, machine learning and artificial intelligence. This paper focuses on the building a Rural Development Classification Model in Python with Scikit-learn. In this work the classification Techniques of Data mining is used to efficiently analyse and predict rural development level and better manage rural economy. This technology can offer vast opportunities and capabilities in rural areas which will in turn help in effectively solving many problems associated with rural areas. Information on rural development is not only crucial but the maintenance and analysis of data is considered one of the main subjects in future decision making and improvement in rural life. Strengthening data collection and analysis provides perhaps the greatest opportunity for researchers and policy makers in rural areas. Utilization of such data is considered a driving force that improves the economic dynamism while creating a new type of knowledge-based economy. Many countries are adopting Data mining applications to Rural Development.

Rural Development (RD), Classification, Clustering, Data Mining (DM); Knowledge Discovery in Databases (KDD)

"Build a Rural Development Classification Model in Python with Scikit-learn", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.113-118, June 2019, Available :http://www.jetir.org/papers/JETIR1906X48.pdf

"Build a Rural Development Classification Model in Python with Scikit-learn", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp113-118, June 2019, Available at : http://www.jetir.org/papers/JETIR1906X48.pdf