1. A computer-implemented method, comprising: accessing a plurality of events, wherein each event in the plurality of events includes a portion of raw machine data; receiving, from a user, a selection of one or more processes for identifying which events to include in a set; wherein the one or more processes selected by the user include at least one of the following: a diverse event-identification process, an outlier event-identification process, a random event identification process, an earliest event-identification process, and a latest event-identification process; for each selected process, identifying events for inclusion in the set using the process; causing display of one or more events in the set of events in a graphical user interface that enables development of a field-extraction rule that specifies how to extract, from the raw machine data included in each of the one or more events, a value for a field that is defined for each of the one or more events, wherein each of the one or more events is searchable using the field; and wherein identifying events for inclusion in the set includes using a process to identify diverse events, and wherein the process to identify diverse events includes: performing a clustering algorithm on a group of events from the plurality of events to form a plurality of clusters, the clustering algorithm placing two events into a same cluster based on similarities in the machine data included in each of the two events; and selecting events from one or more most populous clusters in the plurality of clusters.