Created a model to evaluate cars according to their cost and technical characteristics.
###Code
Code is provided in car_evaluation.py.
This program requres Python 2.7 and the following Python libraries installed:
- NumPy
- Pandas
- matplotlib
- Seaborn
- Scikit-learn
###Data
Dataset used in thie project is included as car.csv and weather.csv. Dataset was obtained from UCI Machine Learning Repository and contains the following attributes.
Price attributes:
buying: buying price (v-high, high, med, low)maint: price of the maintenance (v-high, high, med, low)
Technical characteristics and comfort attributes:
doors: number of doors (2, 3, 4, 5-more)persons: capacity in terms of persons to carry (2, 4, more)lug_boot: the size of luggage boot (small, med, big)safety: estimated safety of the car (low, med, high)
Car class attribute:
class: classification (v-good, good, acc, unacc)