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While running rf.fit(X, y, feature_names=features) in your github code I am getting below error,
: unsupported operand type(s) for /: 'int' and 'RandomForestClassifier'
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* even though I set max_num_rules to 1 I still see more than 1 rule generated
max_num_rules parameter corresponds to underlying glm max_active_predictors, which is used as a stopping criterium to p…
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The current implementation of `rulefit` can sometimes produce redundant features that are then fed into the lasso. This comes from the stochastic nature of random trees and lack of rule pruning.
To…
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#283
sumny updated
4 years ago
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Tree ensmbles now have a new `decision_path` method that rturns a boolean matrix indicating which item falls under which node. At the same time the existing `transform` method on these estimators is b…
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Here is an example of why:
```
X = X.matrix()
rf.fit(X, y, feature_names=features)
```
The function 'fit' accepts a matrix which converts your integers to floats. Then if you have a column with…
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It seems that this package does not support categorical variables? Right?
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Hi,
I wrote detailes as follows:
Many thanks
**H2O version, Operating System and Environment**
R is connected to the H2O cluster:
H2O cluster uptime: 3 seconds 363 millisecon…
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Hello,
I have read the paper "PyExplainer: Explaining the Predictions ofJust-In-Time Defect Models" (ASE2021) in detail and was trying to reproduce the artefact presented.
However I could not get …
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Hello, I am using the pyexplainer to explain the data regarding the bug report. following is my input data :
and the feature data is like this:
and for this pyexplainer is giving output…