Using Precepts to Augment Training Set Learning1
نویسندگان
چکیده
The goal of learning systems is to generalize. Generalization is commonly based on the set of critical features the system has available. Training set learners typically extract critical features from a random set of examples. While this approach is attractive, it suffers from the exponential growth of the number of features to be searched. We propose to extend it by endowing the system with some a priori knowledge, in the form of precepts. Advantages of the augmented system are speed-up, improved generalization, and greater parsimony. This paper presents a precept-driven learning algorithm. Its main features include: 1) distributed implementation, 2) bounded learning and execution times, and 3) ability to handle both correct and incorrect precepts. Results of simulations on real-world data demonstrate promise.
منابع مشابه
Two Kinds of Training Information for Evaluation Function Learning1
This paper identifies two fundamentally different kinds of training information for learning search control in terms of an evaluation function. Each kind of training information suggests its own set of methods for learning an evaluation function. The paper shows that one can integrate the methods and learn simultaneously from both kinds of information.
متن کاملA Precept - Driven Learning Algorithm
Machine learning is an attempt at devising mechanismsthat machines can use to learn, rather than being explicitlyprogrammed for, real-world applications. The goal oflearning systems is to generalize. Generalization is basedon the set of critical features the system has available.Training set learners typically extract critical featuresfrom a random set of examples drawn ...
متن کاملCultural Relativity of Moral Precepts
The foundation of most intellectual discourse is Western-centric to the exclusion of other views. This includes ideal patterns of social interaction, preference for aesthetic, accepted norms and values, and the concepts of dignity, respectability, morality and ethics. Such a position is culturally myopic. Western cultural influence colors all of them including moral precepts. The assumption is ...
متن کاملCS 229 Project: Using Vector Representations to Augment Sentiment Analysis Training Data
While the accuracy of supervised sentiment classification algorithms has steadily increased in recent years, acquiring new human-labeled sentiment data remains expensive. In this paper, we explore the effectiveness of increasing the training data set size for sentiment classification algorithms by adding unlabeled phrases whose sentiments are inferred by their proximity to labeled training phra...
متن کاملRNN-based labeled data generation for spoken language understanding
In spoken language understanding, getting manually labeled data such as domain, intent and slot labels is usually required for training classifiers. Starting with some manually labeled data, we propose a data generation approach to augment the training set with synthetic data sampled from a joint distribution between an input query and an output label. We propose using a recurrent neural networ...
متن کامل