Classification of members in a social networking service

One or more storage media storing instructions which, when executed by one or more processors, cause:

• identifying a particular feature as capable of distinguishing legitimate members of a social network service from a new type of bad actor;
• receiving input that indicates that the particular feature that is not in a set of features upon which a first model is based;
• and
• in response to receiving the input:
• training a plurality of models based on training data and a plurality of features that includes the set of features and the particular feature;
• selecting, based on one or more criteria, a particular model from among the plurality of models that includes a second model that is on of a same type as the first model;
• and
• using the particular model to score a particular data set based on the plurality of features indicated in the particular data set.

A system comprising:

• one or more processors;
• one or more storage media storing instructions which, when executed by the one or more processors, cause:
• identifying a particular feature as capable of distinguishing legitimate members of a social network service from a new type of bad actor;
• receiving input that indicates that the particular feature that is not in a set of features upon which a first model is based;
• in response to receiving the input:
• training a plurality of models based on training data and a plurality of features that includes the set of features and the particular feature;
• selecting, based on one or more criteria, a particular model from among the plurality of models that includes a second model that is of a same type as the first model;
• and
• using the particular model to score a particular data set based on the plurality of features indicated in the particular data set.