Results 11 to 20 of about 247,414 (295)

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

Journal of Translational Medicine, 2021
Background There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information ...
Chris Bauer, Ralf Herwig, Matthias Lienhard, Paul Prasse, Tobias Scheffer, Johannes Schuchhardt   +5 more
doaj   +1 more source

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

BMC Bioinformatics, 2020
Background oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization.
Henry Loeffler-Wirth, Jasmin Reikowski, Siras Hakobyan, Jonas Wagner, Hans Binder   +4 more
doaj   +1 more source

Learning what matters - Sampling interesting patterns [PDF]

, 2017
In the field of exploratory data mining, local structure in data can be described by patterns and discovered by mining algorithms. Although many solutions have been proposed to address the redundancy problems in pattern mining, most of them either ...
M Bhuiyan, M Boley, M Leeuwen van, M Leeuwen van, S Chakraborty, S Shalev-Shwartz, T Calders, V Dzyuba   +7 more
core   +3 more sources

Set-oriented data mining in relational databases [PDF]

, 1995
Data mining is an important real-life application for businesses. It is critical to find efficient ways of mining large data sets. In order to benefit from the experience with relational databases, a set-oriented approach to mining data is needed.
Houtsma, Maurice, Swami, Arun
core   +4 more sources

Interactive Comprehensible Data Mining [PDF]

, 2005
In data mining, or knowledge discovery, we are essentially faced with a mass of data that we are trying to make sense of. We are looking for something “interesting”. Quite what “interesting” means is hard to define, however – one day it is the general trend that most of the data follows that we are intrigued by – the next it is why there are a few ...
Andy Pryke, Russell Beale
openaire   +1 more source

Towards better analysis of machine learning models: A visual analytics perspective

Visual Informatics, 2017
Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users to efficiently solve real-world artificial intelligence and data mining ...
Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu   +3 more
doaj   +1 more source

Weka: A machine learning workbench for data mining [PDF]

, 2005
The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line.
Frank, Eibe, Hall, Mark A., Holmes, Geoffrey, Kirkby, Richard Brendon, Pfahringer, Bernhard, Witten, Ian H.   +5 more
core   +2 more sources

An intelligent assistant for exploratory data analysis [PDF]

, 1997
In this paper we present an account of the main features of SNOUT, an intelligent assistant for exploratory data analysis (EDA) of social science survey data that incorporates a range of data mining techniques.
B. S. Everitt, C. A. O'Muircheartaigh, D. E. Goldberg, J. A. Davis, J. A. Davis, J. Dougherty, J. Fox, J. Healey, J. R. Quinlan, J. R. Quinlan, J. W. Tukey, K. M. Ho, L. Breiman, L. Davis, P. D. Scott, P. D. Scott, U. M. Fayyad, W. J. Frawley   +17 more
core   +2 more sources

vdmR: Generating Web-Based Visual Data Mining Tools with R

Journal of Statistical Software, 2017
The vdmR package generates web-based visual data mining tools by adding interactive functions to ggplot2 graphics. Brushing and linking between multiple plots is one of the main features of this package.
Tomokazu Fujino
doaj   +1 more source

TRIM4Post-Mining: Transition Information Modelling for Attractive Post-Mining Landscapes—A Conceptual Framework

Mining, 2022
TRIM4Post-Mining is a H2020/RFCS-funded project that brings together a consortium of European experts from industry and academia to develop an integrated information modelling system.
Jörg Benndorf, Diego Alejandro Restrepo, Natalie Merkel, Andre John, Mike Buxton, Adriana Guatame-Garcia, Marinus Dalm, Bob de Waard, Hernan Flores, Stefan Möllerherm, Luis Alberto Pizano Wagner, Steffen Schmidt, Andreas Knobloch, Harm Nolte, Martin Kreßner   +14 more
doaj   +1 more source