Let’s begin learning about “What are the Applications of Exploratory Data Analysis in Machine Learning or Predictive Modelling”
Exploratory Data Analysis (EDA) helps in finding hidden information by displaying data in generally two or three dimentions.
It is an approach to analyze data sets to summarize their main characteristics, often with visual methods.
There are a number of tools that are useful for EDA.Nowadays some popular tools for EDA among the data scientist are R and python.
Some techniques used in EDA are:
Principal component analysis
Some Applications are :
1.Finding the data type[continuous/discrete/categorical]
2.Finding multicollinearity issue.
3.Finding the distributions of predictor variables.
5.Finding possibilities for Feature Engineering(process of creating new predictor variables for predictions.)