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In general, over representative training noise should be avoided while under representative training noise is less of a concern.
Due to this, it requires large memory and a more representative training set.
The people are tracked automatically and the representative (training) action classes are labelled by hand.
Generally, the codebooks are generated in advance based on a representative training dataset [10].
Alternatively, given a representative training set, skin detection rules can be determined using machine learning.
In all model-based techniques, the first major issue is to obtain enough representative training data.
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During the past decade, virtual screening (VS) has evolved from traditional similarity searching, which utilizes single reference compounds, into an advanced application domain for data mining and machine-learning approaches, which require large and representative training-set compounds to learn robust decision rules.
Sample-takers of the participating municipalities received a half-day training for the technical procedures of HC 2© sample taking and for informing the attending women of the hrHPV screening and of the implication of their individual randomisation status; the manufacturers' representative trained for 3 days the personnel of the responsible screening laboratory for HC 2© analysis.
Another reason is that a splitting procedure of the sample into training and testing parts may yield non-representative training or testing datasets (we will refer to this as "bad" split of the data).
The misclassification pattern was different for the UCI model, again likely due to the small and non-representative training data.
However, the UCI model performed worse than the rule-based model in predicting HCTLS data, likely because of the very small and non-representative training dataset for the development of the UCI model.
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