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Spectrum Machine Learning Guide
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Welcome
Introduction
Spectrum Machine Learning
A Spectrum Machine Learning Workflow
Machine Learning Stages
Enterprise Designer Stages
Binning
Introduction
Defining Binning Properties
Configuring Basic Options
Binning Output
K-Means Clustering
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Port
Model Metrics Port
Linear Regression
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Ports
Model Score Port
Model Metrics Port
Logistic Regression
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Ports
Model Score Port
Model Metrics Port
Principal Component Analysis
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Port
Model Metrics Port
Random Forest Classification
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Ports
Model Score Port
Model Metrics Port
Random Forest Regression
Introduction
Defining Model Properties
Configuring Basic Options
Configuring Advanced Options
Model Output
Output Ports
Model Score Port
Model Metrics Port
Flow Designer Stages
Binning
How to
Add Binning to workflow
Reference
Stage ports
Binning Properties tab
Basic Options tab
Logistics Regression
How to
Add Logistics Regression to workflow
Reference
Stage ports
Model Properties tab
Basic Options tab
Advanced Options tab
Model Output tab
Principal Component Analysis (PCA)
How to
Add Principal Component Analysis (PCA) to workflow
Reference
Stage ports
Model Properties tab
Basic Options tab
Advanced Options tab
Machine Learning Model Management
Accessing Machine Learning Model Management
Model Assessment
Introduction to Model Assessment
Model Assessment Operations
Model Assessment 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
Binning Management
Introduction to Binning Management
Binning Management Operations
Configuration Settings
Data Science Demonstration Flows
Introduction
Supervised Learning: Loan Default Prediction
Unsupervised Learning: Segmentation
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