Automobile price prediction
IT17104586
P.S.R. Weerasinghe
Weekday Batch
Main Steps:
1) Import the dataset
2) Select colums from the dataset
2) Clean missing data
4) Select needed colums for the prediction
5) Split data (75% for training and 25% for testing)
6) Build a train model applying linear regresion model using traing data
7) Test the predicted value and actual value using a score model
The stats of the predicted values as follows:
Mean 12437.776
Median 10208.7085
Min 5446.8479
Max 34960.6439
Standard Deviation 7323.458
Unique Values 46
Missing Values 0
Feature Type Numeric Score