breast_cancer_clean_target {ascentTraining}

Wisconsin Breast Cancer Database

Description

Wisconsin Breast Cancer Database

Usage

breast_cancer_clean_target

Format

A list containing a training and test dataset. These come from a data frame with 699 observations on 11 variables, however only the target classes have been kept. There is a train to test ratio of 0.8.

Class.Benign

Whether the sample was classified as benign

Class.malignant

Whether the sample was classified as malignant

2. Zhang,J. (1992). Selecting typical instances in instance-based learning. In Proceedings of the Ninth International Machine Learning Conference (pp. 470-479). Aberdeen, Scotland: Morgan Kaufmann.
- Size of data set: only 369 instances (at that point in time)
- Applied 4 instance-based learning algorithms
- Collected classification results averaged over 10 trials
- Best accuracy result:
- 1-nearest neighbor: 93.7%
- trained on 200 instances, tested on the other 169
- Also of interest:
- Using only typical instances: 92.2% (storing only 23.1 instances)
- trained on 200 instances, tested on the other 169

Newman, D.J. & Hettich, S. & Blake, C.L. & Merz, C.J. (1998). UCI Repository of machine learning databases [http://www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.

Source

• Creator: Dr. WIlliam H. Wolberg (physician); University of Wisconsin Hospital ;Madison; Wisconsin; USA

• Donor: Olvi Mangasarian ([e-mail])

• Received: David W. Aha ([e-mail])

These data have been taken from the UCI Repository Of Machine Learning Databases at

• http://archive.ics.uci.edu/ml/datasets.php

• http://www.ics.uci.edu/~mlearn/MLRepository.html

and were converted to R format by Evgenia Dimitriadou.