learning about the seeds dataset we will now look at another agricultural datasetit is still smallbut now too big to comfortably plot exhaustively as we did with iris this is dataset of the measurements of wheat seeds seven features are presentas followsarea (aperimeter (pcompactness length of kernel width of kernel asymmetry coefficient length of kernel groove there are three classes that correspond to three wheat varietiescanadiankomaand rosa as beforethe goal is to be able to classify the species based on these morphological measurements unlike the iris datasetwhich was collected in the sthis is very recent datasetand its features were automatically computed from digital images this is how image pattern recognition can be implementedyou can take images in digital formcompute few relevant features from themand use generic classification system in later we will work through the computer vision side of this problem and compute features in images for the momentwe will work with the features that are given to us uci machine learning dataset repository the university of california at irvine (ucimaintains an online repository of machine learning datasets (at the time of writingthey are listing datasetsboth the iris and seeds dataset used in this were taken from there the repository is available online