Score predictive tool is giving negative values for a positive target variable

Question

Hi,

I am having an assignement in my class.

I am creating a predictive model for bike usage of the dataset from the bixi

https://www.bixi.com/en/page-27

we have to create a model that predict the usage of the bike, so we have to predict the number bike user per hour and have been given some dataset.

1. bike usage (from bixi)

2. temperature dataset

I have  created the model below for prediction.

I have added attached a sample of the dataset as the input of the model (a blended dataset from bix and temprature file).

The problem is that the model created is predicting negative values while it shouldn't (the nomber of passenger cannot be negative!!)

Any help, thanks!

Bixi - Prediction Model.yxmd

sample dataset.csv

fa5fou5 · Answer

I was doubting on how to implement the time variable.

To make it even clear. we can even make a distinction between two differents model:

1. Weekend demand

2. Weekday demand

So Yes the Start hour is not linear with the desired response but it DOES have an effect on the nomber of user.

Which bring an Idea to me but I don't know how to implement it.

The IDEA:

is there a way to make a regression model with the two variables :

1. Tempreture

2. Humidity %

Then adjust the response with a weight factor depending on the hour of the day, (I dont know if we can use the decision tree for that, and if there is way for it)

fa5fou5 · Answer

Thanks for giving me an insight on how to read the coefficients values.
I was confused on how to read them!

AngelosPachis · Answer

As a final side note @fa5fou5 , I would be tempted to increase the % of data used for the evaluation/creation of the model from around 35 that it is currently to around 60, and the validation to be around 25-30%.

The evaluation batch should always be significantly larger than the validation one for a successful/trustworthy prediction.

Hope that helps,

Angelos