User Guide# 1. Analysis 1.1. Decomposition: decomposition 1.2. Dimensionality: dimensionality 1.3. Model selection with Probabilistic PCA and Factor Analysis (FA): factor 2. Base Accessors and Estimators 2.1. Data 2.2. Missing 2.3. Sequential Backward Selection 2.4. Greedy Perceptron 2.5. Majority Vote Classifier 2.6. Adaline Gradient Descent 2.7. Adaline Gradient Descent with Batch 3. Case Histories 3.1. Features 3.2. Prepare 3.3. Processing 4. Datasets 4.1. DC-Datasets 4.2. Learning Dataset 4.3. EDI dataset 4.4. Boilerplate function : fetch_data() 4.5. Generate ERP or VES data 5. Methods 5.1. DC-Resistivity: electrical 5.2. EM: em 5.3. Hydrogeology: hydro 6. Utilities 6.1. Core Utilities: coreutils 6.2. Math Extension Utilities: exmath 7. View 7.1. Params space plots: plot 7.2. Learning space plots: mlplot