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1
Introduction
2
Data
3
Data Preparation
4
Exploratory Plot
5
Relationships
6
Stratifying
7
Decision trees
8
Pause
9
Collecting metrics
10
Looking at the results
11
Best for the tree result
12
Lastfit
13
Graph
14
Tree partitions
15
Points
16
Geom jitter
17
Geom part tree
18
Visualization
19
Metrics
20
Slopes
21
Results
22
Summary
Description:
Learn to model Canadian wind turbine capacity using decision trees and the tidymodels framework in this 40-minute tutorial. Explore data preparation, create exploratory plots, and analyze relationships within the #TidyTuesday wind turbine dataset. Dive into stratifying data, tuning decision trees, and collecting metrics to evaluate model performance. Visualize tree partitions, interpret results, and gain insights into predicting wind turbine capacity. Follow along with the provided code on Julia Silge's blog to enhance your understanding of decision tree modeling and data analysis techniques.

Model Canadian Wind Turbine Capacity With Decision Trees and Tidymodels

Julia Silge
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