This course covers the skills required to develop, assess, and score predictive models using the Partition platform and the Neural platform.

Aprenda a

• explore data graphically
• build and understand predictive models such as decision trees and neural network models
• compare and explain complex models
• score new data in JMP and generate SAS score code.

A quién va dirigido

Data analysts, qualitative experts, and others who want an introduction to predictive modeling using JMP Pro

Formatos disponibles	Duración
Presencial:	1.0 día
Live Web:	4 sesiones de medio día

Before attending this course, it is recommended that you complete the JMP Software: A Case Study Approach to Data Exploration and JMP Software: Statistical Decisions Using ANOVA and Regression courses or have equivalent experience.

Este curso utiliza JMP software.

Introduction to Predictive Modeling

• supervised classification
• regression
• honest assessment using holdout data
• assessment plots and statistics

Exploring Data

Predictive Modeling with the Partition Platform

• recursive partitioning
• optimizing model complexity
• model fit statistics
• statistical graphics

Predictive Modeling with Neural Networks

• optimizing model complexity
• interpreting models
• model fit statistics
• statistical graphics
• k-fold crossvalidation
• boosted neural networks

Tree Advanced Topics

• instability of trees
• boosted trees
• bootstrap forest
• comparing models