region based algorithm process mining 2

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  K-means Clustering: Algorithm, Applications, Evaluation …

  2018917 · In this post, we will cover only Kmeans which is considered as one of the most used clustering algorithms due to its simplicity. Kmeans Algorithm Kmeans algorithm is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups (clusters) where each data point belongs to only one group.

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  CPU mining in 2021 – List of CPU mineable coins & CPU only algorithms

  202181 · CPU mining is a process that utilizes CPU (Central Processing Unit) cores to verify transactions on the blockchain and to create / mine new coins. CPU mining involves using everyday computers or setting up CPU mining rigs to make use of their power mainly as a mining devices.

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  Awesome Process Mining with Python - GitHub

  Inspired by awesome-python. What is Process Mining (PM) ? process of extracting valuable information from event logs/databases that are generated by processes.* process discovery: analysing event data to see how a process actually looks like conformance checking: comparing mined process to the reference model (=the process how it should be)

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  Process Mining: Data Science in Action | SpringerLink

  About this book. This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on ...

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  Data Mining Algorithms – 13 Algorithms Used in Data Mining

  2024622 · We will cover all types of Algorithms in Data Mining: Statistical Procedure Based Approach, Machine Learning-Based Approach, Neural Network, Classification Algorithms in Data Mining, ID3 Algorithm, C4.5 Algorithm, K Nearest Neighbors Algorithm, Naïve Bayes Algorithm, SVM Algorithm, ANN Algorithm, 48 Decision Trees, Support …

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  Training Region-based Object Detectors with Online Hard Example Mining

  2016413 · The field of object detection has made significant advances riding on the wave of region-based ConvNets, but their training procedure still includes many heuristics and hyperparameters that are costly to tune. We present a simple yet surprisingly effective online hard example mining (OHEM) algorithm for training region-based ConvNet detectors.

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  Sensors | Free Full-Text | Efficient Algorithm for …

  2021721 · This method determines the time and location of rare-earth mining activities by analyzing the time sequence trajectory of rare-earth disturbance areas and tracking the progress of vegetation recovery in the mining areas over time. This method is applied in the headwaters region of the Dongjiang River in Gannan, China.

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  Image Segmentation by Region Based and Watershed Algorithms

  2009316 · First, two region-based image segmentation techniques are described: region growing and split and merge. Second, the watershed transform, which combines aspects of both edge-based and region-based segmentation approaches, is described. In general, the basic watershed transform leads to an over-segmentation of an image.

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  Process Mining: Data science in Action | Coursera

  Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because ...

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