7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system.
7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system. 10. The system of claim 7 , wherein selecting the first of test data from the data samples comprises selecting the top n th ranked data samples where n is an integer greater than one.