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In contrast, our approach is based on supervised machine learning.
Here, we employ classifiers that are based on supervised machine leaning, where a training set is applied for each classifier.
The suitable database design plays a vital role in any kind of problem based on supervised machine learning.
Automatic emotion recognition systems based on supervised machine learning require reliable annotation of affective behaviours to build useful models.
For instance, Anvik and Murphy (2011) proposed an approach based on supervised machine learning that requires training to create a classifier.
It seems likely that existing methods to handle coordination based on supervised machine learning, such as [35], would be effective in many of these cases.
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Most of the existing tumor classification approaches are based on supervised learning, such as support vector machines or decision trees, which aimed at identifying genetic features to distinguish two or more known tumor (sub- types [ 49, 50].
Most of the recent reliability analysis methods are based on supervised learning approaches, e.g. neural network, support vector machine, importance sampling (IS), Markov Chain Monte Carlo (MCMC), subset simulation (SS), etc.
As compared to other hyper-heuristics based on supervised learning such as decision tree [107, 127], logistic regression [57], support vector machine [129], and artificial neural networks [32, 138], genetic programming (GP) has shown a number of key advantages.
Based on supervised trial value, the supervised trial median residue (STMR) in tomatoes was 0.069 mg/kg (Table 2).
The process itself relies purely on the tweet (text) which is segmented based on supervised learning.
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