Abstract: A model generation apparatus includes a processor that is configured to: acquire information data for learning, acquire document data for learning, extract a first portion and a second portion having a lower rate of match with the information data than the first portion from the document data based on a rate of match between the information data and each portion of the document data, generate a first machine learning model by using first learning data in which first data for learning included in the information data is used as input data and the first portion is used as correct answer data, and generate a second machine learning model by using second learning data in which second data for learning included in the information data is used as input data and the second portion is used as correct answer data.

Abstract: There is provided an information processing method, an information processing apparatus, and a program capable of preparing a high performance model for an unknown introduction destination facility even in a case where a domain of the introduction destination facility is unknown at a step of training a model. The information processing method includes: dividing a dataset, which indicates a behavior of a user on an item for each of combinations of a plurality of the users and a plurality of the items, into a plurality of subgroups that are robust with respect to domain shift; generating a local model for performing a prediction of the behavior of the user on the item for each of the subgroups; and combining a plurality of the local models generated for each of the subgroups.

Abstract: An information processing apparatus includes at least one processor, in which the processor is configured to: for a machine learning model that uses a document data group including a plurality of document data as input and outputs output data, derive an evaluation value in the machine learning model for each document data included in the document data group.

Abstract: An information processing apparatus including: plural models including at least a first model that uses first data as input to carry out a first prediction task and a second model that uses second data as input to carry out a second prediction task different from the first prediction task, and at least one processor, in which the processor is configured to: acquire information data representing information related to a specific target; select a selection model to be used for prediction from among the plural models based on the information data; and derive a degree of importance to the specific target for each item included in the information data by using the selection model.

Abstract: Disclosed is an electrophotographic photoreceptor having a high sensitivity, a high endurance and a high stability against repeated use which comprises a conductive support with a light-sensitive layer containing one or more hydrazone compounds represented by the following formula (I): ##STR1## wherein R.sub.1 represents an alkyl group of 5 or more carbon atoms, R.sub.2 represents a substituted or unsubstituted alkyl group, alkenyl group, aralkyl group, aryl group or heterocyclic group, and R.sub.3 and R.sub.4 each represent a hydrogen atom, an alkyl group, an alkoxy group or a halogen atom.