We present a RapidMiner extension for OpenML, an open science platform for sharing machine learning datasets, algorithms and experiments. In order to share machine learning experiments as easily as possible, it is being integrated into various popular data mining and machine learning tools, including RapidMiner. Through this plugin, data can be downloaded, and workflows and results uploaded to ...

All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. Machine learning : a probabilistic perspective / Kevin P. Murphy. p. cm. — (Adaptive computation and machine learning series) Includes bibliographical references a...

Modern machine learning methods are increasingly powerful and opaque. This opaqueness is a concern across a variety of domains in which algorithms are making important decisions that should be scrutable. The explainabilty of machine learning systems is therefore of increasing interest. We propose an explanation-byexamples approach that builds on our recent research in Bayesian teaching in which...

Businesses are increasingly interested in how big data, artificial intelligence, machine learning, and predictive analytics can be used to increase revenue, lower costs, and improve their business processes. In this paper, we describe how we have developed a data-driven machine learning method to optimize the collection process for a debt collection agency. Precisely speaking, we create a frame...

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

The increased volume of information available in digital form and the need of organizing it has generated and progressively intensified the interest in automatic text categorization. A widely used research approach to this problem is based on machine learning techniques: an inductive process builds a classifier by automatically learning the characteristics of the categories. Machine learning is...

Abstract The diameter distribution of trees in a stand provides the basis for determining stand’s ecological and economic value, its structure stability appropriate management practices. Scots pine ( Pinus sylvestris L.) is one most common important conifers Turkey, so well-planned schedule critical. Diameter models to accurately describe help improve strategies, but developing reliable require...

Describes the mechanical, electronic and software design of a 10-DOF bipedal robot which has been constructed to study control, parameterisation and automatic expansion of the stability envelope of a complex real-time behaviour, namely, dynamically-balanced two-legged walking. The machine is physically complete and demonstrates reasonable reliability in movement control including dynamically-ba...

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...