Despite prowess of the support vector machine, it is not specifically designed to extract features relevant to the prediction. For example, in network intrusion detection, we need to learn relevant network statistics for the network defense. In consu...
In our previous statistics tutorials, we have treated population parameters as fixed values, and provided point estimates and confidence intervals for them. An alternative approach is the Bayesian statistics. It treats population parameters as random...
A variation of the standard definition of Kendall correlation coefficient is necessary in
order to deal with data samples with tied ranks. It known as the Kendall’s tau-b
coefficient and is more effective in determining whether two non-parametric data samples with ties are correlated.
In our last tutorial on SVM training with GPU, we mentioned a necessary step to pre-scale the data with rpusvm-scale, and to reverse scaling the prediction outcome. This cumbersome procedure is now simplified with the latest RPUSVM. read more
Most elementary statistical inference algorithms assume that the data can be modeled by a set of linear parameters with a normally distributed noise component. A new class of algorithms called support vector machine (SVM) remove such constraint. rea...
The correlation coefficient is a measurement of correlation between two random variables. While its computation is straightforward, it is not readily applicable to non-parametric statistics. read more
With the distance matrix found in previous tutorial, we can use various techniques of cluster analysis for relationship discovery. For example, in the data set mtcars, we can run the distance matrix with hclust, and plot a dendrogram that displays a ...
With the distance matrix found in previous tutorial, we can use various techniques of cluster analysis for relationship discovery. For example, in the data set mtcars, we can run the distance matrix with hclust, and plot a dendrogram that displays a ...
Statistics is computationally intensive. Routine statistical tasks such as data extraction, graphical summary, and technical interpretation all require heavy use of modern computing machinery. Obviously, these tasks can benefit greatly from a paralle...
In hypothesis testing, a type II error is due to a failure of rejecting
an invalid null hypothesis. The probability of avoiding a type II error is
called the power of the hypothesis test, and is denoted by the quantity
1 - β .
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
