J
Jeff Heaton
Researcher at Nova Southeastern University
Publications - 16
Citations - 686
Jeff Heaton is an academic researcher from Nova Southeastern University. The author has contributed to research in topics: Artificial neural network & Feature engineering. The author has an hindex of 10, co-authored 16 publications receiving 426 citations. Previous affiliations of Jeff Heaton include Washington University in St. Louis.
Papers
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Journal ArticleDOI
Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning
TL;DR: Deep Learning provides a truly comprehensive look at the state of the art in deep learning and some developing areas of research, aimed at an academic research audience with prior knowledge of calculus, linear algebra, probability, and some programming capabilities.
Proceedings ArticleDOI
An empirical analysis of feature engineering for predictive modeling
TL;DR: In this article, the authors report on empirical research to demonstrate what types of engineered features are best suited to which machine learning model type, by generating several datasets that are designed to benefit from a particular type of engineered feature.
Proceedings ArticleDOI
Comparing dataset characteristics that favor the Apriori, Eclat or FP-Growth frequent itemset mining algorithms
TL;DR: In this paper, the authors explored the effects that two dataset characteristics can have on the performance of the three most common algorithms for frequent itemset mining, namely, Apriori, Eclat, and FP-Growth.
Proceedings ArticleDOI
An Empirical Analysis of Feature Engineering for Predictive Modeling
TL;DR: This paper reports on empirical research to demonstrate what types of engineered features are best suited to which machine learning model type, by generating several datasets that are designed to benefit from a particular type of engineered feature.
Book
Programming Neural Networks with Encog 2 in Java
TL;DR: This book introduces you to Encog, an advanced neural network programming framework that allows you to create a variety of neural network architectures using the Java programming language.