one standard dataset in machine learning is the newsgroup datasetwhich contains , posts from different newsgroups among the groupstopics are technical ones such as comp sys mac hardware or sci crypt as well as more politicsand religion-related ones such as talk politics guns or soc religion christian we will restrict ourselves to the technical groups if we assume each newsgroup is one clusterwe can nicely test whether our approach of finding related posts works the dataset can be downloaded from jrennie/ newsgroups much more simplehoweveris to download it from mlcomp at scikit already contains custom loaders for that dataset and rewards you with very convenient data loading options the dataset comes in the form of zip filedataset- - news- _wjqig zipwhich we have to unzip to get the folder which contains the datasets we also have to notify scikit about the path containing that data directory it contains metadata file and three directories testtrainand raw the test and train directories split the whole dataset into percent of training and percent of testing posts for conveniencethe dataset module also contains the function fetch_ newsgroupswhich downloads that data into the desired directory the website finding the right dataset to tune your machine-learning program and exploring how other people use particular dataset for instanceyou can see how well other people' algorithms performed on particular datasets and compare them either you set the environment variable mlcomp_datasets_home or you specify the path directly with the mlcomp_root parameter when loading the dataset as followsimport sklearn datasets mlcomp_dir " :\datadata sklearn datasets load_mlcomp(" news- "mlcomp_ root=mlcomp_dirprint(data filenamesarray([' :\\data\\ \\raw\\comp graphics\\ - '' :\\data\\ \\raw\\comp graphics\\ - '' :\\data\\ \\raw\\alt atheism\\ - '' :\\data\\ \\raw\\rec sport hockey\\ - '' :\\data\\ \\raw\\sci crypt\\ - '