1. A computer-implemented method for improving the classification accuracy of trustworthiness classifiers, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying a set of training data that is available for training trustworthiness classifiers used by a security software product to classify computing resources as clean or malicious, wherein: the set of training data comprises at least one of: data that is collected from a plurality of different organizations; and data that is specific to a plurality of different organizations; identifying the set of training data comprises: identifying at least one computing resource whose trustworthiness remained unknown for a certain amount of time after having been encountered by at least one organization within the plurality of different organizations; collecting information about the computing resource while the computing resource's trustworthiness remained unknown; and after collecting the information about the computing resource, classifying the computing resource as clean or malicious; identifying a specific organization whose computing systems implement the security software product; selecting, based at least in part on a characteristic of the specific organization, a subset of training data from the set of training data that is available for training trustworthiness classifiers; training a trustworthiness classifier for the specific organization using: the subset of training data selected based at least in part on the characteristic of the specific organization; the information about the computing resource collected while the computing resource's trustworthiness remained unknown; and the computing resource's classification as clean or malicious; and applying, by way of the security software product, the trustworthiness classifier to at least one computing resource encountered by the specific organization to classify the computing resource as clean or malicious.