Mention some of the EDA Techniques?

4 years ago
Machine Learning

Exploratory Data Analysis (EDA) helps analysts to understand the data better and forms the foundation of better models. 
Visualization

  • Univariate visualization
  • Bivariate visualization
  • Multivariate visualization
    Missing Value Treatment – Replace missing values with Either Mean/Median
    Outlier Detection – Use Boxplot to identify the distribution of Outliers, then Apply IQR to set the boundary for IQR
    Transformation – Based on the distribution, apply a transformation on the features
    Scaling the Dataset – Apply MinMax, Standard Scaler or Z Score Scaling mechanism to scale the data.
    Feature Engineering – Need of the domain, and SME knowledge helps Analyst find derivative fields which can fetch more information about the nature of the data
    Dimensionality reduction — Helps in reducing the volume of data without losing much information
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Sanisha Maharjan
Sanisha Maharjan
Jan 12, 2022
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