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FIND-S: FINDING A MAXIMALLY SPECIFIC HYPOTHESIS

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  FIND-S: FINDING A MAXIMALLY SPECIFIC HYPOTHESIS •         To illustrate this algorithm, assume the learner is given the sequence of training examples from the EnjoySport task. Step 1: Initialize h to the most specific hypothesis in H FIND-S: Step-2 ·        The first step of FIND-S is to initialize h to the most specific hypothesis in H h - (Ø, Ø, Ø, Ø, Ø, Ø) ·        Consider the first training example x1 = <Sunny, Warm, Normal, Strong, Warm, Same>, + •         Observing the first training example , it is clear that hypothesis h is too specific. None of the " Ø " constraints in h are satisfied by this example, so each is replaced by the next more general constraint that fits the example h1 = <Sunny, Warm, Normal, Strong, Warm, Same> ·        Consider the second training example x2 = <Sunny, Warm, H...

WEEK 2: • Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file.

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WEEK 2: • Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file.  FIND - S Algorithm Data Set: