Decision trees have proved to be valuable tools for the description, classification and
generalization of data. Work on constructing decision trees from data exists in multiple …

What are decision trees? | Nature Biotechnology Skip to main content Thank you for visiting
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State-of-the-art decision tree methods apply heuristics recursively to create each split in
isolation, which may not capture well the underlying characteristics of the dataset. The …

Abstract We present Deep Neural Decision Forests-a novel approach that unifies
classification trees with the representation learning functionality known from deep …

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …

Machine learning applications such as finance and medicine demand accurate and
justifiable predictions, barring most deep learning methods from use. In response, previous …

Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

This paper develops a novel tree-based algorithm, called Bonsai, for efficient prediction on
IoT devices–such as those based on the Arduino Uno board having an 8 bit ATmega328P …

Decision Forests Page 1 Decision Forests A Unified Framework for Classification,
Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning Full text …

Pattern recognition has long been studied in relation to many different (and mainly
unrelated) applications, such as remote sensing, computer vision, space research, and …