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final team project1

Logistic Regression Predictor
Logistic Regression Learner
Random Forest Learner
Logistic Regression Predictor
ROC Curve
Changes ? values in race to Unknown to make results more readable.
Rule Engine
Scorer
ROC Curve
ROC Curve
ROC Curve
partitions data into training and test
Table Partitioner
Normalizes large columns like num lab procedures and num medications to prevent bias in logistic regression as large values can lead to bias.
Normalizer
Scorer
ROC Curve
Scorer
Decision Tree Predictor
Decision Tree Learner
Scorer
Random Forest Predictor
ROC Curve
ROC Curve
Random Forest Learner
Scorer
Color Manager
Color Manager
Age could be translated into values from 1 to 10. Weight is almost always missing. Payer code and medical specialty is usually missing.
CSV Reader
Statistics
Too many missing weight values for it to be a useful feature and removing ids that could lead to bias. Payer code and medical specialty are missing over 50% of the time so those were also removed.
Column Filter
Hidden test set
CSV Reader
Changes ? values in race to Unknown to make results more readable.
Rule Engine
Logistic Regression Learner
CSV Reader
Number to String
String Replacer
Math Formula
Column Filter
Missing Value
Rule Engine
One to Many
Number to String
Low Variance Filter
Table Partitioner
Rule Engine
Column Filter
Random Forest Predictor
Normalizes large columns like num lab procedures and num medications to prevent bias in logistic regression as large values can lead to bias.
Normalizer
Scorer
Decision Tree Learner
Too many missing weight values for it to be a useful feature and removing ids that could lead to bias. Payer code and medical specialty are missing over 50% of the time so those were also removed.
Column Filter
Decision Tree Predictor
Changes diag 1 back to String
Number to String
Logistic Regression Predictor
Removes .0 values that were a holdover from changing a float to a string, but keeps decimals.
String Manipulation

Nodes

Extensions

Links