Click here: Bike Rental Prediction.
The objective of this Case is to Predication of bike rental count on daily based on the environmental and seasonal settings.
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Exploratory Data Analysis
- Loading the dataset and libraries
- Data cleaning
- Typecasting the attributes
- Missing value analysis
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Attributes distributions and trends
- Monthly distribution of counts
- Yearly distribution of counts
- Outliers analysis
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Normality test
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Correlation matrix
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Split the dataset into train and test dataset
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Encoding the categorical features
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Modelling the training dataset
- Linear Regression Model
- Decision Tree Regressor Model
- Random Forest Model
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Cross Validation Prediction
- Linear Regression CV Prediction
- Decision Tree Regressor CV Prediction
- Random Forest CV Prediction
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Model performance on test dataset
- Linear Regression Prediction
- Decision Tree Regressor Prediction
- Random Forest Prediction
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Model Evaluation Metrics
- R-squared score
- Root mean square error
- Mean absolute error
11.Choosing best model for predicting bike rental count