Train a random forest using DecisionTrees on bootstrap samples where each sample has a random subset of dimensions but the split point is performed using a minimum entropy criteria. More...
Inheritance diagram for ml_lib.random_forest.RFRandomInputSubset:
Public Member Functions | |
| def | train |
| def | transform_input |
Public Attributes | |
| learners | |
| number_of_dimensions | |
Detailed Description
Train a random forest using DecisionTrees on bootstrap samples where each sample has a random subset of dimensions but the split point is performed using a minimum entropy criteria.
Definition at line 70 of file random_forest.py.
Member Function Documentation
| def ml_lib.random_forest.RFRandomInputSubset.train | ( | self, | |
| dataset | |||
| ) |
Reimplemented from ml_lib.random_forest.RFBase.
Definition at line 71 of file random_forest.py.
| def ml_lib.random_forest.RFRandomInputSubset.transform_input | ( | self, | |
| input, | |||
tree = None |
|||
| ) |
Definition at line 89 of file random_forest.py.
Member Data Documentation
Definition at line 71 of file random_forest.py.
Reimplemented from ml_lib.random_forest.RFBase.
Definition at line 71 of file random_forest.py.
The documentation for this class was generated from the following file: