Most of the time floating point arithmetic does
approximately the right thing.  When adding sums or having products
of numbers that greatly differ in magnitude, the floating point
arithmetic may be incorrect.  This package implements the Kahan
(1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum
<doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from 'NumPy',
See Castaldo (2008) <doi:10.1137/070679946> for a discussion of
accuracy), and arbitrary precision sum (adapted from the fsum in
'Python' ; Shewchuk (1997)
<https://people.eecs.berkeley.edu/~jrs/papers/robustr.pdf>).  In addition,
products are changed to long double precision for accuracy, or
changed into a log-sum for accuracy.

Computational Prediction of Proteins Encoded by Circadian Genes
A computational model for predicting proteins encoded by circadian genes. The support vector machine has been employed with Laplace kernel for prediction of circadian proteins, where compositional, transitional and physico-chemical features were utilized as numeric features. User can predict for the test dataset using the proposed computational model. Besides, the user can also build their own training model using their training dataset, followed by prediction for the test set.

Recent years have seen an increased interest in novel methods
for analyzing quantitative data from experimental psychology. Currently, however, they lack an
established and accessible software framework. Many existing implementations provide no guidelines,
consisting of small code snippets, or sets of packages. In addition, the use of existing packages
often requires advanced programming experience. 'PredPsych' is a user-friendly toolbox based on
machine learning predictive algorithms. It comprises of multiple functionalities for multivariate
analyses of quantitative behavioral data based on machine learning models.
plyr, ggplot2, caret, rpart, e1071, mclust, MASS, party,
randomForest

plyr, ggplot2, caret, rpart, e1071, mclust, MASS, party,
randomForest, statmod