EBOC: Ensemble-Based Ordinal Classification in Transportation

Table 1

The basic characteristics of the transportation datasets. (I: number of instances, A: number of attributes, C: number of classes).

Dataset	I	A	C	Class Distribution	Target Attribute	Data Preprocessing
Auto MPG	398	8	3	131-134-133	mpg	Removing the columns with unique values (i.e., car name)
Automobile	205	26	7	0-3-22-67-54-32-27	symboling	-
Bike Sharing	17379	13	3	5797-5783-5799	cnt	Removing the columns “instant,” “dteday,” “casual,” and “registered”
Car Evaluation	1728	7	4	1210-384-69-65	class	-
Car Sale Advertisements	9309	10	3	3112-3080-3117	price	Removing rows with zero price value
NYS Air Passenger Traffic	1584	4	3	528-528-528	total passengers	Removing the columns “Domestic” and “International Passengers”
Road Traffic Accidents (2017)	2203	13	3	1879-309-15	casualty severity	(i) Removing columns that hold reference numbers; (ii) Splitting date column into day and month
SF Air Traffic Landings Statistics	21105	14	3	6941-7103-7061	landing count	-
SF Air Traffic Passenger Statistics	18398	12	3	6132-6133-6133	passenger count	-
Smart City Traffic Patterns	48120	6	3	15687-16436-15997	vehicles	(i) Removing ID column; (ii) Splitting date column into day, month, and year
Statlog (Vehicle Silhouettes)	846	19	4	212-217-218-199	class	-
Traffic Volume Counts (2012-2013)	5945	31	3	1983-1989-1973	traffic volume at 11:00 -12:00AM	(i) Removing the columns with unique values (i.e., ID, Segment ID); (ii) Splitting date column into day, month, and year