Made Correlation and Confusion Matrices for Enhanced Model Evaluation #5

[YuwanshB005]

First i did Data Preprocessing which included handling null values

1. 

I filled these null values in body and acidity column with their Median values and also removed unnecessary rows

Then i handled Categorical features using Label Encoding

Then i did Data Visualisation to get more understanding of data, outliers and Unnecessary columns

I created Co-relationa Matrix to to remove unnecessary Features

Then i plotted several plots to get idea of outliers

Then i removed the outliers using Interquartile Range (IQR) Method.

Then i split my data into training and testing Datasets and used Feature Scaling (Standardisation) to to get all in data between -3 to 3 so that model can perform good

Then i used GridSearchCV on multiple Models To find the best accuracy with best parameters

Afterwards i Predicted to output from my testing dataset and then i made confusion matrix to check where out prediction and real value differs and evaluate the performance of model

[YuwanshB005]

@darshbaxi Please Review

[Samcoding5854]

Good work. Appreciate the detailed PR description Could have converted the e values to integers in the matrice. There is a parameter to be checked True for this.