Machinehack-Mathcothon-Car-Price-Prediction

Leaderboard standing: 55 out of 2400 participants

About Data

With the rise in the variety of cars with differentiated capabilities and features such as model, production year, category, brand, fuel type, engine volume, mileage, cylinders, colour, airbags and many more, we are bringing a car price prediction challenge for all. We all aspire to own a car within budget with the best features available. To solve the price problem we have created a dataset of 19237 for the training dataset and 8245 for the test dataset.

Dataset Description

Train.csv - 19237 rows x 18 columns (Includes Price Columns as Target)
Attributes
    ID
    Price: price of the care(Target Column)
    Levy
    Manufacturer
    Model
    Prod. year
    Category
    Leather interior
    Fuel type
    Engine volume
    Mileage
    Cylinders
    Gear box type
    Drive wheels
    Doors
    Wheel
    Color
    Airbags
Test.csv - 8245 rows x 17 columns
Sample Submission.csv -Please check the Evaluation section for more details on how to generate a valid submission 

Skills

Multivariate Regression
Big dataset, underfitting vs overfitting
Optimizing RMSLE to generalize well on unseen data

Evaluation

What is the Metric In this competition? How is the Leaderboard Calculated ?

The submission will be evaluated using the RMSLE metric. One can use np.sqrt(mean_squared_log_error(actual, predicted)) to calculate the same
This hackathon supports private and public leaderboards
The public leaderboard is evaluated on 70% of Test data
The private leaderboard will be made available at the end of the hackathon which will be evaluated on 100% of Test data
The Final Score represents the score achieved based on the Best Score on the public leaderboard

How to Generate a valid Submission File

Sklearn models support the predict() method to generate the predicted values

You should submit a .csv file with exactly 8245 rows with 1 column(Price). Your submission will return an Invalid Score if you have extra columns or rows.

The file should have exactly 1 column.

Note: Do not shuffle the sequence of the test series

Using Pandas:

submission_df.to_csv('my_submission_file.csv', index=False)

Link: https://machinehack.com/hackathons/data_hack_mathcothon_car_price_prediction_challenge/overview