Classical conditioning applies to <u>voluntary behavior</u>, while operant conditioning applies to <u>involuntary </u><u>behavior</u>.
Classical conditioning links an automatic or voluntary response to a stimulus. Operant conditioning includes incentives as well as rewards for the learner, whereas classical conditioning does not.
Unconscious learning occurs during classical conditioning. When you learn through classical conditioning, a predetermined stimulus is matched with an instinctive conditioned response. Thus, a behaviour is produced.
Operant conditioning is a form of associative learning in which the strength of a behaviour is altered by reward or punishment. It is also a method that is employed to facilitate such learning.
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Answer:
What we can infer from these sentence from the story is:
D. The volunteers planned to connect the refrigerators to a source of electricity.
Explanation:
We can choose the correct option via elimination, after reading the passage. At no point does the passage say anything that would lead us to think the cords and fridges would be used as weapons. Letter A is, thus, eliminated. It also does not mention the amount of time necessary to install all the 60 fridges. We can also eliminate letter B for that reason. Letter C is also wrong, since the lines do not provide us with information about fridges being broken. It is likely some were, but not because we can infer it from the passage.
<u>Letter D is the only correct option. We can infer the volunteers were planning on plugging the fridges to an outlet. Why? Because they were carrying extension cords. That was the whole purpose of carrying them. Otherwise, the fridges wouldn't work. Therefore, we can safely choose letter D.</u>
Answer:
yearn to possess or have (something).
Explanation:
yearn to possess or have (something).
Answer:
Advantages of society: Discipline - it comes forward when order needs to be in place, people are able to incorporate discipline as accountability for action. Formation or Order - compromise and healthy conversation and agreement form for each member to get what they want and experience what they need.
A Temporal Investigation of Crash Severity Factors in Worker-Involved Work Zone Crashes: Random Parameters and Machine Learning Approaches:
Reason:
In the context of work zone safety, worker presence and its impact on crash severity has been less explored. Moreover, there is a lack of research on contributing factors by time-of-day. To accomplish this, first a mixed logit model was used to determine statistically significant crash severity contributing factors and their effects. Significant factors in both models included work-zone-specific characteristics and crash-specific characteristics, where environmental characteristics were only significant in the daytime model. In addition, results from parameter transferability test provided evidence that daytime and nighttime crashes need to be modeled separately. Further, to explore the nonlinear relationship between crash severity levels and time-of-day, as well as compare the effects of variables to that of the logit model and assess prediction performance, a Support Vector Machines (SVM)
What is meant by machine learning approach?
Machine Learning is an AI technique that teaches computers to learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model.
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