Answer:
Kindly check Explanation.
Explanation:
Machine Learning refers to a concept of teaching or empowering systems with the ability to learn without explicit programming.
Supervised machine learning refers to a Machine learning concept whereby the system is provided with both features and label or target data to learn from. The target or label refers to the actual prediction which is provided alongside the learning features. This means that the output, target or label of the features used in training is provided to the system. this is where the word supervised comes in, the target or label provided during training or teaching the system ensures that the system can evaluate the correctness of what is she's being taught. The actual prediction provided ensures that the predictions made by the system can be monitored and accuracy evaluated.
Hence the main difference between supervised and unsupervised machine learning is the fact that one is provided with label or target data( supervised learning) and unsupervised learning isn't provided with target data, hence, it finds pattern in the data on it's own.
A to B mapping or input to output refers to the feature to target mapping.
Where A or input represents the feature parameters and B or output means the target or label parameter.
"Sleeping is an effect of <span>Depressants, but agitation may cause a person to wake up"</span><span />
C because previous sends you back to something before such as a web page, Next does the opposite and I can't remember what Show MarkUp does.
Answer:
visual encoding
Explanation:
According to my research on the three types of encoding methods, I can say that based on the information provided within the question Kaydence is best described as capitalizing on visual encoding. Which is the act of associating a certain something with a picture in order to store it into memory, as opposed of associating it with sound or words. In this situation Kaydence is associating it with a networking diagram she drew.
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