In our project, we selected a dataset (hereafter referred to as the Mushroom dataset which categorizes mushroom types as either poisonous or edible based on various attributes such as gill-color, cap-shape and odor) from UCI’s machine learning repository: https://archive.ics.uci.edu/ml/datasets/mushroom. For our KDD techniques, we have decided to use Clustering, Random Forests and Bayesian classifiers.
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View Code? Open in Web Editor NEWClassification analysis on UCI's Mushroom dataset. Three methods are used to classify mushroom toxicity: K-means, Naive Bayes and Random Forest