Calendar · Lecture Notes
MIT OpenCourseWare
Data Mining
Art: Gaston, John, (John Gaston merchant ledger) - DPLA -…, 1773 · Public domain
- Instructor
- Prof. Nitin Patel
- Term
- Spring 2003
- Level
- Graduate
- What's inside
- 1 lecture note · 27 other files · 5 web pages
- Materials open
- MIT OCW
About this course
Source: MIT OpenCourseWare 15.062 Data Mining, Spring 2003, Prof. Nitin Patel — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.
Materials are grouped the way MIT organized them. A verified, course-wide order has not been established here.
Has MIT solutions
Before you start
Prerequisites are not listed here. Check MIT's own syllabus for this course.
How this course was organized
What's here, and what isn't
- A lecture sequence of 19 items is confirmed. It stays as organized materials rather than a full course order.
Not included here
5 items from the source could not be safely included:
- MIT's page format for this item wasn't recognized clearly enough to place it safely. (5 items)
Materials by section
Grouped by section, as MIT organized them. Not sequenced or ordered.
Lecture Notes
14 files
- Data Mining Overview Download
- Prediction and Classification with k-Nearest Neighbors Example 1: Riding Mowers Download
- Classification and Bayes Rule, Naïve Bayes Download
- Classification Trees Download
- Discriminant Analysis Example 2: Fisher’s Iris data Download
- Logistic Regression Case Download
- Handlooms Download
- Neural Nets Download
- Multiple Regression Review Download
- Multiple Linear Regression in Data Mining Download
- Regression Trees, Case: IBM/GM weekly returns Comparison of Data Mining Techniques Download
- k-Means Clustering, Hierarchical Clustering Download
- Principal Components Download
- Association Rules (Market Basket Analysis) Download
Assignments
- CBC 4000 (CBC_4000.xls) Download
- Problem 2: The German Credit Case Read the case and answer all the questions at the end Download
- German Credit Case Data Download
- Bond Rating Problem 1 (romyBondRatingProb1.xls) Download
- Regression Problem 3 (romyRegressionProb3.xls) Download
- Normals Problem 4 (romyBiVarNormProb4.xls) Download
Exams
Study Materials
Other materials from this course
Course outline
Calendar · Lecture Notes
Lecture 2: Classification and Bayes Rule, Naïve Bayes
Calendar · Lecture Notes
Lecture 3: Classification Trees
Calendar · Lecture Notes
Lecture 4: Discriminant Analysis
Calendar · Lecture Notes
Lecture 5: Logistic Regression Case: Handlooms
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Lecture 6: Neural Nets
Calendar · Lecture Notes
Lecture 7: Cases: Direct Marketing/German Credit
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Lecture 8: Assessing Prediction Performance
Calendar · Lecture Notes
Lecture 9: Subset Selection in Regression
Calendar · Lecture Notes
Lecture 10: Regression Trees, Case: IBM/GM weekly returns
Calendar · Lecture Notes
Lecture 11: k-Means Clustering, Hierarchical Clustering
Calendar · Lecture Notes
Lecture 12: Case: Retail Merchandising
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Lecture 13: Midterm Exam
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Lecture 14: Principal Components
Calendar · Lecture Notes
Lecture 15: Guest Lecture by Dr. Ira Haimowitz: Data Mining and CRM at Pfizer
Calendar · Lecture Notes
Lecture 16: Association Rules (Market Basket Analysis)
Calendar · Lecture Notes
Lecture 17: Recommendation Systems: Collaborative Filtering
Calendar · Lecture Notes
Lecture 18: Guest Lecture by Dr. John Elder IV, Elder Research: The Practice of Data Mining
Calendar · Lecture Notes
Lecture 19: Project Presentations
MIT OpenCourseWare, Prof. Nitin Patel, 15.062 Data Mining, Spring 2003.
License: CC BY-NC-SA 4.0 · Edition: Spring 2003 · Open the original course on OCW ↗
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