Project: Product search relevance score prediction using Home Depot Dataset
Mini Projects:
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Implementation of ID3 algorithm
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Analysis of different Classifiers in ML: • Decision Trees • Perceptron (Single Linear Classifier) • Neural Net • Support Vector Machines • Naive Bayes Classifiers
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Implementation of Naive Bayes learning algorithm for binary classification tasks
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Performance comparison of following classifiers available in ML: Logistic Regression, k-Nearest Neighbors, Bagging, Random Forests, AdaBoost
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Modification of ID3 Algorithm Instead of using the ID3 algorithm to choose which attribute to select for splitting the data at each node, write a method that randomly picks attributes for each node. Construct a new tree using random selection of attributes and compare the performance (in terms of accuracy) of the tree constructed using this approach to the one constructed using ID3. You need to compare the trees without pruning.
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Extracting and Analyzing Social Media Data using Facebook and Twitter.