Machine Learning Laboratory for 6th Sem VTU Artificial Intelligence and Machine Learning 2018 Scheme
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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 and show the output for test cases. Develop an interactive program by Compareing the result by implementing LIST THEN ELIMINATE algorithm.
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For a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Eliminationalgorithm. Output a description of the set of all hypotheses consistent with the training examples.
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Demonstrate Pre processing (Data Cleaning, Integration and Transformation) activity on suitable data: For example: Identify and Delete Rows that Contain Duplicate Data by considering an appropriate dataset. Identify and Delete Columns That Contain a Single Value by considering an appropriate dataset.
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Demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge toclassify a new sample.
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Demonstrate the working of the Random forest algorithm. Use an appropriate data set for building and apply this knowledge toclassify a new sample.
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Implement the naïve Bayesian classifier for a sample training data set stored as a .CSV file. Compute the accuracy of the classifier, considering few test data sets.
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Assuming a set of documents that need to be classified, use the naive Bayesian Classifier model to perform this task. Calculate the accuracy, precision, and recall for your data set.
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Construct a Bayesian network considering medical data. Use this model to demonstrate the diagnosis of heart patients using standard Heart Disease Data Set.
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Demonstrate the working of EM algorithm to cluster a set of data stored in a .CSV file.
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Demonstrate the working of SVM classifier for a suitable data set.