Patent ID: 11893499
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 18:
19. A computer implemented method for developing and training models for analyzing data, the method comprising:
constructing a model by:
receiving, by one or more computer processors, a training data set;
growing, by the one or more computer processors, a random forest of decision trees from the training data set;
determining, by the one or more computer processors, Out-of-bag (OOB) predictions for an instance of the data set for the random forest;
appending the Out-of-bag predictions as a probability vector to the training data set as new features represented in columns for the instance of the training data set by the one or more computer processors;
determining, by the one or more computer processors, a first OOB accuracy for the random forest;
growing, by the one or more computer processors, an additional random forest using the training data set with the appended OOB predictions;
determining, by the one or more computer processors, a second OOB accuracy for the additional random forest;
comparing, by the one or more computer processors, the first OOB accuracy of the random forest and the second OOB accuracy of the additional random forest; and
combining an output of the additional random forest by the one or more computer processors with a combiner.