It is shown, that by monitoring the inference process via measures such as entropy or Kullback Leibler divergence, one can determine when to stop the data collection process.
Inference engine has a role of controlling the searching knowledge base, executing the rules and tracking the inference process by using the depth-first searching method.
Therefore, it is of importance to strengthen the quality of the inference process by guiding it as much as possible with data corresponding to various angles of approach.
From a correlation of 0.794 it is worthy to proceed with further improvements by integrating more data into the inference process.
We repeated the inference process by using the data from each data source for the WinDTome creation.
Finally, we took into account that uncertainty in the inference process by bootstrapping 1,000 times the control dataset.
Hypotheses constructed during the inference process, by the design of the system (see below), correspond to the annotation concepts that capture discriminating knowledge.
This paper refines and extends recent approaches to the automatic schema inference by exploiting an obsolete schema in the inference process, designing new MDL measures and heuristic excluding of eccentric data inputs.
In addition, the predicted GRN showed a high reliability, since 10 predicted edges were independently validated by literature findings after completion of the inference process.
The inference process of maximum throughput is differentiated by τ in (15).
