The graphs also are useful for determination of sensitivity to the prior inputs.
Since the classification analysis was performed without the prior inputs on tissue origin, these results strongly suggest that PA usage, similar to gene expression profiles, also exhibits tissue-specific signatures.
The algorithms do not assume any prior input distribution and the running times hold with high probability.
Users of unsupervised analysis try to find internal structure in the data set without any prior input knowledge.
It is supposed that the prior external input information is given with proportional uncertainties.
Prior input to unsupervised hierarchical clustering, the gene expression was standardised.
While not suited as stand-alone detection algorithms in all cases, these methods can provide regions of interest with sufficiently high confidence to allow higher-level, object-based classification methods to use them as prior input.
However, it depends on prior input, and this dependence does not decrease as sample size increases, unlike parameter's estimation based on posterior distributions [ 20].
In contrast to combinational logic, whose outputs depend only on the current inputs, sequential logic outputs depend on both current and prior inputs.
Sequential logic remembers information about prior inputs.
