The Inductive Miner is another common algorithm used in process mining to discover process models from event logs. This technique relies on the idea of cutting event logs into smaller sub-logs called cuts or splits and then detecting various cuts on the directly followed graphs created using the...
2 # Generate an array of `ARRAY_LENGTH` items consisting 3 # of random integer values between 0 and 999 4 array = [randint(0, 1000) for i in range(ARRAY_LENGTH)] 5 6 # Call the function using the name of the sorting algorithm 7 # and the array you just created 8 run_sorting_...
Metaheuristic algorithms have wide applicability, particularly in wireless sensor networks (WSNs), due to their superior skill in solving and optimizing ma
This dataset was mainly created to achieve fire/not fire images classification and fire images segmentation. Also, they could be used to perform fire detection from RGB and thermal UAV imagery. Fire detection 360-degree dataset The fire detection 360-degree dataset [11] is another dataset that ...
Upsampling works in the opposite way—new samples are created and inserted to increase the frequency of a signal. For example, if an extra sample was inserted after every sample in a 10 Hz signal, it would become a 20 Hz signal. The difficult part is knowing what to insert! There’s no...
However, the group should also be able to switch its behavioral mode, provided this change is a positive one and the group has ways of knowing so. One can observe that stability and adaptability are principles that go hand-in-hand and the best strategy to approach, is to safely explore a...
Theoutputs? Whatvariablesshould be created, and whatinitial valuesshould they have? What intermediate steps should be taken to compute other values and to ultimately compute the output? Do these steps repeat instructions that can be written in simplified form using a loop?
The models created for each sample of the data are therefore more different than they otherwise would be, but still accurate in their own unique ways. Combining their predictions results in a better estimate of the true underlying output value....
Limiting the number of expensive operations done in the loop body is a good way to speed up the entire loop. A typical array-processing loop can be created using any of the three faster loop types. The code is most frequently written as follows: //original loops for (var i=0; i < ...
And fourth, the over-fitting problem, which is often observed in the models with millions of parameters such as DBNs, and the under-fitting problem, which occurs often in deep networks, can be effectively addressed by the generative pre-training step. An insightful analysis on what speech ...