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Machine Learning Guide
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Welcome
Introduction
Machine Learning Module
A Machine Learning Workflow
Binning
Introduction to Binning
Configuring Basic Options
Binning Output
Binning Lookup
Introduction to Binning Lookup
Defining Binning Properties
Binning Output
K-Means Clustering
Introduction to K-Means Clustering
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Linear Regression
Introduction to Linear Regression
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Logistic Regression
Introduction to Logistic Regression
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Principal Component Analysis
Introduction to Principal Component Analysis
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Random Forest Classification
Introduction to Random Forest Classification
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Random Forest Regression
Introduction to Random Forest Regression
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Java Model Scoring
Introduction to Java Model Scoring
Defining Model Properties
Model Output
Machine Learning Model Management
Introduction to Machine Learning Model Management
Accessing Machine Learning Model Management Model Analysis
Model Management Model Analysis Operations
Model Detail Tab
K-Means Clustering Details
Logistic Regression Details
Linear Regression Details
Random Forest Regression Details
Random Forest Classification Details—Binomial
Random Forest Classification Details—Multinomial
Principal Component Analysis Details
Data Science Demonstration Flows
Introduction
Supervised Learning: Loan Default Prediction
Unsupervised Learning: Segmentation
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