The data set comes from the Kaggle Digit Recognizer competition. The goal is to recognize digits 0 to 9 in handwriting images. Because the original data set is large, I have systematically sampled 10% of the data by selecting the 10th, 20th examples and so on. You are going to use the sampled data to construct prediction models using multiple machine learning algorithms that we have learned recently: naïve Bayes, kNN and SVM algorithms. Tune their parameters to get the best model (measured by cross validation) and compare which algorithms provide better model for this task.
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