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procedure.txt
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procedure.txt
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*********************STEPS THAT I FOLLOWED****************************************
1. IMPORTING THE DATASETS:
Imported the training and testing datasets using pandas .read_csv() function.
2. EXPLORATORY DATA ANALYSIS:
a)Placed all the missing values in a seperate list.
b)Placed all thenumeric, categorical and discrete values in different lists.
c)Visualized numerical features with line plot from matplotlib.
d)Visualized continousfeatures with histogram from matplotlib.
3.FEATURE ENGINEERING:
a) Replace all the missing values with the mean of their respective field.
b) Encoded Object datatypes using Label Encoder from sklearn
4. FEATURE SCALING:
a) Scaled all the data with standard scaler from sklearn.
5.MODEL FITTING:
a) Split the data into training and test sets.
b)Trained the model using XGBoost Regressor.
c) hyperparameter tuning with RandomsearchCV.
d) Stored the predictions in 'MySubmission.csv'.
Regards,
varunpusarla@gmail.com