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40 lines
1.6 KiB
Plaintext
Executable File
40 lines
1.6 KiB
Plaintext
Executable File
1. Title: Teaching Assistant Evaluation
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2. Sources:
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(a) Collector: Wei-Yin Loh (Department of Statistics, UW-Madison)
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(b) Donor: Tjen-Sien Lim (limt@stat.wisc.edu)
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(b) Date: June 7, 1997
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3. Past Usage:
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1. Loh, W.-Y. & Shih, Y.-S. (1997). Split Selection Methods for
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Classification Trees, Statistica Sinica 7: 815-840.
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2. Lim, T.-S., Loh, W.-Y. & Shih, Y.-S. (1999). A Comparison of
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Prediction Accuracy, Complexity, and Training Time of
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Thirty-three Old and New Classification Algorithms. Machine
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Learning. Forthcoming.
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(ftp://ftp.stat.wisc.edu/pub/loh/treeprogs/quest1.7/mach1317.pdf or
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(http://www.stat.wisc.edu/~limt/mach1317.pdf)
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4. Relevant Information:
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The data consist of evaluations of teaching performance over three
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regular semesters and two summer semesters of 151 teaching assistant
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(TA) assignments at the Statistics Department of the University of
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Wisconsin-Madison. The scores were divided into 3 roughly equal-sized
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categories ("low", "medium", and "high") to form the class variable.
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5. Number of Instances: 151
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6. Number of Attributes: 6 (including the class attribute)
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7. Attribute Information:
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1. Whether of not the TA is a native English speaker (binary)
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1=English speaker, 2=non-English speaker
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2. Course instructor (categorical, 25 categories)
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3. Course (categorical, 26 categories)
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4. Summer or regular semester (binary) 1=Summer, 2=Regular
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5. Class size (numerical)
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6. Class attribute (categorical) 1=Low, 2=Medium, 3=High
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8. Missing Attribute Values: None
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