TRAINING INDUCTIVE LOGIC PROGRAMMING ENHANCED DEEP BELIEF NETWORK MODELS FOR DISCRETE OPTIMIZATION

摘要

#$%^&*AU2017203299B220190214.pdf#####5 ABSTRACT TRAINING INDUCTIVE LOGIC PROGRAMMING ENHANCED DEEP BELIEF NETWORK MODELS FOR DISCRETE OPTIMIZATION System and method for training inductive logic programming enhanced 10 deep belief network models for discrete optimization are disclosed. The system initializes (i) a dataset comprising values and (ii) a pre-defined threshold, partitions the values into a first set and a second set based on the pre-defined threshold. Using Inductive Logic Programming (ILP) engine and a domain knowledge associated with the dataset, a machine learning model is constructed on the first set and the 15 second set to obtain Boolean features, and using the Boolean features that are being appended to the dataset, a deep belief network (DBN) model is trained to identify an optimal set of values between the first set and the second set. Using the trained DBN model, the optimal set of values are sampled to generate samples. The predefined threshold is adjusted based on the generated samples, and the steps are 20 repeated to obtain optimal samples. [To be published with FIG. 2] 28IliL 1NU. U1 011GGL . J) Initializing (i) a dataset comprising a plurality of values and (ii) a pre-defined threshold 202 Partitioning the plurality of values into a first set of values and a _ 204 second set of values based on the pre-defined threshold Constructing, using (i) an Inductive Logic Programming and (ii) a domain knowledge associated with the dataset, a machine learning model on each of the first set of values and the second ' 206 set of values to obtain one or more Boolean features Training, using the one or more Boolean features that are being appended to the dataset, a deep belief network (DBN) model to identify an optimal set of values between the first set of values 208 and the second set of values Sampling, using the trained DBN model, the optimal set of values to generate one or more samples 210 FIG. 2