Influence of X-data over the Output Predictor Y-data

In general we use to choose different x-data (input variable or input feature) to predict our output(predictor).

Sometime, we might choose more than one x-data (input variable or input feature) to predict the output.

But, at the same time some of the x-data(input variable) we choose to predict may not have that influence over the output.

So, it high time that we check the influence of x-data over the output using below mentioned methods:

1. Co-relation co-efficient
2. ANOVA (Analysis of Variance)

Same can also be visualised using the graph called

1. Scatter plot

Same can also be analysed using inbuilt sklearn libraries mentioned below.

1. Linear Regression (finding coefficient)
2. Gradient Boosting and Random Forest