Model Example¶ Data Preprocessing Data Schema Loading Data World Map Projection Statistical Summary Missing Value Feature Engineering Classification Table of Contents 1. Train-Test Data Preparation 2. Missing Value Processing 3. Data Processing 4. Model Selection 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 Table of Contents Data Preparation Data Selection Feature Engineering Model Selection Hyper-Parameters Specification Data Results 2 dimensions graphs of data 3 dimensions graphs of data Decomposition T-distributed Stochastic Neighbor Embedding (T-SNE) Table of Contents 1. T-distributed Stochastic Neighbor Embedding (T-SNE) 2. Preparation 3. NAN value process 4. Feature engineering 5. Model Selection 6. T-SNE Network Analysis