Data-Preprocessing-Template
A simple template to process your data in an optimal form for you to use in machine learning/regression models
Libraries Required
For this template you will need to install the following libraries using pip install libraryName
- Pandas
- Numpy
- sklearn
In addition the
csvfile should have the dependant varaible at the last column
Funtion Description
The code contains one main function namely
dataPreprocess(dataset,test_size,random_state,feature_scaling)
Return Values
This function returns four outputs:
X_train: The test set of dependant values needed to train your model which is plotted on the X-axis.y_train: The test set of independant values needed to train your model which is plotted on the Y-axis.X_test: The test set of dependant values for which you shall test your model against.y_test: The test set of dependant values for which you shall test your model against.
Parameters
dataset: This is the name of the csv file containing the dataset. Do not forget to add.csvwith your file name.test_size: This is to decide the ratio of test data to training data you want to divide your data into. Its default value is 0.8(80%).random_state: This parameter determines how randomly the data is divided. Its default value is 0.feature_scaling: Set to True if you want to standardize your data range of the dependant and independant varaibles.
Citation
Code idea inspired from Machine Learning A-Z™: Hands-On Python & R In Data Science.
Contact
For more details contact me at moonisrasheed18@gmail.com