Model Example

• Data Preprocessing
  • Loading Data
  • World Map Projection
  • Statistical Summary
  • Missing Value
  • Feature Engineering
• Classification
  • 1. Train-Test Data Preparation
  • 2. Model Selection
  • 3. Results
• Regression
  • 1. Introduction to Regression
  • 2. Introduction to Regression function of Geochemistry π
    • 2.1 Enter the sub-menu of Regression
    • 2.2 Generate a map projection
    • 2.3 Enter the range of data and check the output
    • 2.4 Use imputation techniques to deal with the missing values
    • 2.5 Feature Engineering
  • 3. Regression Model-Running
• Clustering
  • Modle Selection
  • Hyper-Parameters Specification
  • Results
  • 2 dimensions graphs of data
  • 3 dimensions graphs of data
• Decomposition
  • Principal Component Analysis (PCA)
  • Preparation
  • NAN value process
  • Feature engineering
  • PCA