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docs

daily_worksheets/Daily Exercises

EX-4-20.docxEX-IV-4-6.docxEX-IX-4-18.docxEX-VI-4-11.docxEX-VII-4-13.docxEX-X-4-20.docxEx-5-2.docxEx-I-3-28.docxEx-II-3-30.docxEx-III-4-4.docxEx-V-4-11.docxEx-VIII-4-13.docx

lectures

Final Examination and Paper.pdfLecture 1 - Introduction and Expectations.pdfLecture 10- Overfitting.pdfLecture 11 - More on Entropy.pdfLecture 12 - Association Rule Mining - Apriori.pdfLecture 13 - Rule Interestingness.pdfLecture 14 - Basic Clustering.pdfLecture 15 - Sequence Mining.pdfLecture 16 - Rule Induction - PRISM Algorithm.pdfLecture 17 - More On Clustering.pdfLecture 2 - Overview of Data Mining.pdfLecture 3 - Data Set Quality and Sources of Data, Descriptive Statistics.pdfLecture 4 - Naïve Bayes and Nearest Neighbor Classification.pdfLecture 5 - Decision Tree Induction.pdfLecture 6 - Entropy based Tree Induction.pdfLecture 7 - Frequency Tables GINI Index and 𝜒^2 for Attribute Selection.pdfLecture 8 - Estimating Classifier Accuracy.pdfLecture 9 - Continuous Attributes.pdf

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