Project Title: Occupancy Classification Data
Background:
You are given sensor data of an office such as light, temperature, humidity, and CO2 measurements. There is also an attribute to indicate whether the room is occupied. In this way, we could analyze the data for patterns and apply a linear regression model to predict whether the room is occupied.
Objectives:
The objectives of this project are:
Data Set Information:
Each record in the data set consists of 8 attributes:
Attribute |
Attribute description |
index |
record index |
date |
record date time year-month-day hour:minute:second |
Temperature |
In Celsius |
Humidity |
In % |
Light |
In Lux |
CO2 |
In ppm |
Humidity Ratio |
Derived quantity from temperature and relative humidity, in kg water-vapor/kg-air |
Occupancy |
, 0 or 1, 0 for not occupied, 1 for occupied status |
Detail: https://github.com/LuisM78/Occupancy-detection-data
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