Now, we need three high dimensional datasets (500 to 1000 features) with small sample size (< 500 samples) for our project. Therefore, we will run our feature selection algorithm on these datasets. If you have any ideas and links that can download, It could be great for us...
I used to get involved in cardiac atlas project. There is open access medical imaging data which are high dimensional. The idea is to use the imaging data to classify the patients in different heart disease. More detail in http://www.cardiacatlas.org/
You can find in KEEL-dataset repository the most used dataset in machine learning and classification.
http://sci2s.ugr.es/keel/datasets.php
http://sci2s.ugr.es/keel/category.php?cat=clas
Hello Salih,
You can visit the following link to find 262 datasets for classification with different characteristics such as number of features, objects and classes.
http://archive.ics.uci.edu/ml/datasets.html?format=&task=cla&att=&area=&numAtt=&numIns=&type=&sort=nameUp&view=table
Hello Salih,
I think Gene Expression microarray is a good choice for you, the features may range from 6000 to 60000 feature
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