- Structured data modelling.
- Data preprocessing.
- Feature extraction and dimensionality reduction including principal component analysis.
- Similarity measures and summary statistics.
- Visualization and interpretation of models.
- Overfitting and generalization.
- Classification (decision trees, nearest neighbor, naive Bayes, neural networks, and ensemble methods.)
- Linear regression.
- Clustering (k-means, hierarchical clustering, and mixture models.)
- Association rules.
- Density estimation and outlier detection.
- Applications in a broad range of engineering sciences.
All material including software are intended for research and educational purpose. Any sale or commercial distribution is strictly forbidden, unless the Department of Applied Mathematics and Computer Science, the Technical University of Denmark (DTU Compute) has given explicit permission.
The material including software is provided "as-is". Support is generally not available. No warranties of any kind, express or implied, are made as to it or any medium it may be on. No remedy will be provided for indirect, consequential, punitive or incidental damages arising from it, including such from negligence, strict liability, or breach of warranty or contract, even after notice of the possibility of such damages.
Inquiries to the Cognitive System Section, DTU Compute, http://cogsys.compute.dtu.dk
The material is not for redistribution.
The apriori method included in the toolbox is taken from http://www.borgelt.net/apriori.html, for details of the algorithm see also http://www.borgelt.net/doc/apriori/apriori.
Description of the datasets in the Data folder:
body.mat This is a subset of the dataset on body dimenstions available at http://www.sci.usq.edu.au/courses/STA3301/resources/Data/ and described in G. Heinz, L. J. Peterson, R. W. Johnson, and C. J. Kerk, “Exploring relationships in body dimensions,” Journal of Statistics Education, vol. 11, no. 2, 2003.
faithful.mat and faithful.txt Dataset on eruption of the Old Faithful geyser described in A. Azzalini and A. Bowman, “A look at some data on the old faithful geyser,” Applied Statistics, pp. 357–365, 1990. W. Härdle, Smoothing techniques: with implementation in S. Springer, 1991
female.txt and male.txt Data is taken from http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/nlp/corpora/names/, Please consult the accompanying readme_male_female.txt file in the Data folder.
iris.xls Fisher's Iris data, for a description see also http://en.wikipedia.org/wiki/Iris_flower_data_set. The data has been downloaded from http://archive.ics.uci.edu/ml/datasets/Iris.
nanonose.xls This data has been taken from the nanonose project, see also http://www.nanonose.dk, it is described in T. S. Alstrøm, J. Larsen, C. H. Nielsen, and N. B. Larsen, “Data-driven modeling of nano-nose gas sensor arrays,” in SPIE Defense, Security, and Sensing. International Society for Optics and Photonics, 2010, pp. 76 970U–76 970U.
StopWords A txt file of list of common words provided in the TMG toolbox.
textDocs.txt This example of documents for a term-document matrix is taken from L. Eldén, Matrix Methods in Data Mining and Pattern Recognition. Philadelphia, PA, USA: Society for Industrial and Applied Mathematics, 2007.
Wine.mat and Wine2.mat P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis. Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547–553, 2009. downloaded from http://archive.ics.uci.edu/ml/datasets/Wine+Quality Wine2 is same as Wine but with some outliers removed.
zipdata.mat and digits.mat USPS handwritten digits availabe at http://www.cad.zju.edu.cn/home/dengcai/Data/MLData.html, see also J. J. Hull, “A database for handwritten text recognition research,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 16, no. 5, pp. 550–554, 1994.
wildfaces.mat and wildfaces_grayscale.mat Taken from http://tamaraberg.com/faceDataset/ and described in Tamara L. Berg, Alexander C. Berg, Jaety Edwards, David A. Forsyth Neural Information Processing Systems (NIPS), 2004. The wildfaces.mat is an extract with 1000 examples of the original dataset and wildfaces_grayscale a gray scale converted version of these 1000 examples taken from the original data.
messy_data.data This dataset is an excerpt of the Auto MPG Data Set which has been heavily formatted to introduce comming data preprocessing isusues. Revised from CMU StatLib library, data concerns city-cycle fuel consumption https://archive.ics.uci.edu/ml/datasets/auto+mpg This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the 1983 American Statistical Association Exposition.