{'fraction_non_alphanumeric': 0.021705426356589147, 'fraction_numerical': 0.01627906976744186, 'mean_word_length': 5.004651162790697, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Special issue on the eighteenth international conference on machine learning (icml2001)

The papers in this issue were selected from among those presented at the Eighteenth International Conference on Machine Learning (ICML2001) held in Williamstown, Massachusetts, June 28 July 1, 2001. To create this issue, all authors of ICML2001 were given the opportunity to submit an expanded version of their conference paper, which then went through the standard rigorous review process of JMLR. The twelve papers contained in this issue were selected out of a total of 23 submissions. As can be seen from the wide range of topics in the selected papers, this special issue shows the breadth of topics covered in the field of machine learning today. Each article presents in-depth analysis and experimentation from a different area of machine learning. We hope that you enjoy reading this issue as much as we enjoyed preparing it. Finally, we would like to thank all authors for their contributions, and the reviewers for their help in bringing this special issue to its current form. Special thanks go to Craig Codrington, Alan Fern, Matthew Greig, Matthew Harrison, Melanie Mitchell, Christina Pavlopoulou, Jon Shapiro and Xiaoli Zhang for helping with the final copy-edit of the accepted papers.