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Fig. 2 | Animal Biotelemetry

Fig. 2

From: Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Fig. 2

Decision-tree algorithm used for the classification of behaviours in dairy cows. Decision rules are evaluated downwards until the final behavioural class is assigned. The scheme contains the feature characteristic used as data input for the decision rule to partition the data. At each decision rule, data is partitioned into clusters with similar properties. The first decision rule in this algorithm discriminates between high and low energy expenditure activities using the overall dynamic body acceleration (VeDBA). High energy expenditure activities are classified as feeding. Low energy expenditure activities are further classified using a second decision rule which discriminates data by the static component of the acceleration in the y-axis (SCAY). Data with values above threshold B (−0.055 g) are classified as standing and data with values below this threshold are classified as lying

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