Predicting Bike Rentors' Membership -- Bike
This dataset comes from a bike sharing service in the United States. This dataset requires you to exercise your pro data munging skills. The data is provided quarter-wise from 2010 (Q4) onwards. Each file has 7 columns. It is a classification problem.
The objective is the exploration of the Capital Bikes Share Trip Dataset. I intend to explore the data, look at and plot the relationship between the variables. This is a classification issue that will make use of the Logistic Regression Algorithm to predict the likelihood that a certain combination of the Independent variables lead to a certain classification.
I shall explore a good number of hypothesis and deduce conclusions based on the output of the plots.
Some feasible hypothesis include but not limited to:
There is a relationship between the duration one stays with a bike and their membership type There is a link between the End station and the Member Type Most members start at Station Number 31014 There is no link between the duration one stays with a bike and an End station number