| Name : R-Buddle
| |
| Version : 2.0.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.3.15
| Date : 2024-09-12 10:43:35
|
| Group : Development/Libraries/Other
| Source RPM : R-Buddle-2.0.1-lp153.3.15.src.rpm
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| Size : 0.47 MB
| |
| Packager : (none)
| |
| Summary : A Deep Learning for Statistical Classification and Regression Analysis with Random Effects
|
Description :
Statistical classification and regression have been popular among
various fields and stayed in the limelight of scientists of those
fields. Examples of the fields include clinical trials where the
statistical classification of patients is indispensable to predict the
clinical courses of diseases. Considering the negative impact of
diseases on performing daily tasks, correctly classifying patients
based on the clinical information is vital in that we need to identify
patients of the high-risk group to develop a severe state and arrange
medical treatment for them at an opportune moment. Deep learning - a
part of artificial intelligence - has gained much attention, and
research on it burgeons during past decades: see, e.g, Kazemi and
Mirroshandel (2018) < DOI:10.1016/j.artmed.2017.12.001>. It is a
veritable technique which was originally designed for the
classification, and hence, the Buddle package can provide sublime
solutions to various challenging classification and regression problems
encountered in the clinical trials. The Buddle package is based on the
back-propagation algorithm - together with various powerful techniques
such as batch normalization and dropout - which performs a multi-layer
feed-forward neural network: see Krizhevsky et. al (2017)
< DOI:10.1145/3065386>, Schmidhuber (2015)
< DOI:10.1016/j.neunet.2014.09.003> and LeCun et al. (1998)
< DOI:10.1109/5.726791> for more details. This package contains two main
functions: TrainBuddle() and FetchBuddle(). TrainBuddle() builds a
feed-forward neural network model and trains the model. FetchBuddle()
recalls the trained model which is the output of TrainBuddle(),
classifies or regresses given data, and make a final prediction for the
data.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
