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classifications

Suppose that a learning algorithm is trying to find a consistent hypothesis when the classifications of examples are actually random. There are n Boolean

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Suppose that a learning algorithm is trying to find a consistent hypothesis when the classifications of examples are actually random. There are n Boolean attributes, and examples are drawn uniformly from the set of 2^n possible examples. Calculate the number of examples required before the probability of finding a contradiction in the data reaches 0.5. 

Review or familiarize yourself with the types and classifications of drugs on the?SAMHSA

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To prepare for this Discussion: Review or familiarize yourself with the types and classifications of drugs on the SAMHSALinks to an external site. Web site. Review Chapter 17, “Drug Courts,” in the course text Handbook of Forensic Mental Health with Victims and Offenders: Assessment, Treatment, and Research. Reflect on the different approaches for treating drug offenders in forensic … Read more

Assess the importance of standardized terminologies and classifications that are important in a clinical setting.

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Assess the importance of standardized terminologies and classifications that are important in a clinical setting.Compare and contrast the similarities and differences between clinical communication and information exchange.Determine the significance and focus of HL7.Evaluate the impact of using standardized clinical terminology to enter patient information into an EHR.