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An implementation of of the CART-ANOVA algorithm for regression trees in Python

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.idea
.idea
 
 
__pycache__
__pycache__
 
 
data
data
 
 
r
r
 
 
CpTable.py
CpTable.py
 
 
README.md
README.md
 
 
Usage.docx
Usage.docx
 
 
Usage.pdf
Usage.pdf
 
 
anova.py
anova.py
 
 
best_split.py
best_split.py
 
 
data_handler.py
data_handler.py
 
 
make_cp_table.py
make_cp_table.py
 
 
node.py
node.py
 
 
partition.py
partition.py
 
 
print_tree.py
print_tree.py
 
 
pypart.py
pypart.py
 
 
pypart_to_rpart.py
pypart_to_rpart.py
 
 
runmany.py
runmany.py
 
 
timings_prethreading.txt
timings_prethreading.txt
 
 
tree_params.py
tree_params.py
 
 
xval.py
xval.py
 
 

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pypart

An implementation of of the CART-ANOVA algorithm for regression trees in Python

Description

A Python implementation of the CART algorithm using only ANOVA splitting and split selection criteria. Produces output that can be imported into R as an rpart object.

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An implementation of of the CART-ANOVA algorithm for regression trees in Python

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machine-learning cart rpart

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