This project aims to predict room occupancy based on sensor data. The dataset contains attributes such as date, temperature, humidity, light, CO2, humidity ratio, and occupancy. The exploratory data analysis shows correlations between temperature, light, CO2, and occupancy. The Random Forest Classifier is used as the final model with an accuracy score of 98%.
- #data-science#data-analysis#classification#data-visualization#random-forest#exploratory-data-analysis
Table of contents
Room Occupancy DetectionData DictionaryData PreprocessingExploratory Data AnalysisCorrelation Between the VariablesData Preprocessing 2Train Test SplitModel BuildingModel EvaluationTesting the Model on the New DatasetConclusion32 Impressions