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This document outlines a term project for the course CS 739 Spatial Data Mining, focusing on applying data mining techniques to analyze real-world crime data. The project includes an empirical study for crime prediction using various statistical methods and classification/regression approaches, working with datasets that track different types of crime in Boston over specified time periods.
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CS 739 spatial data refers to a form or document used by certain organizations to report geographic information related to land use, zoning, and planning.
Entities involved in land development, planning departments, and organizations that manage geographic data within a specific jurisdiction are typically required to file CS 739 spatial data.
To fill out CS 739 spatial data, you must gather relevant geographic and planning information, complete the form according to the guidelines provided by the filing authority, and ensure all required sections are filled accurately.
The purpose of CS 739 spatial data is to collect and organize data related to land use planning, enabling effective decision-making and analysis regarding geographic information systems.
Information reported on CS 739 spatial data typically includes data on geographic boundaries, land use type, zoning classifications, and any relevant environmental considerations.
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Relevant keywords

crime forecasting data mining spatial data mining crime prediction statistical analysis CSV data classification algorithms regression algorithms Boston crime data empirical study

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