1. A predictive modeling apparatus comprising: a memory configured to store a machine-executable module encoding a predictive modeling procedure, wherein the predictive modeling procedure includes a plurality of tasks, wherein the machine-executable module includes a directed graph representing dependencies between the tasks, and wherein the plurality of tasks includes at least one pre-processing task, at least one model-fitting task, and at least one post-processing task; and at least one processor configured to execute the machine-executable module, wherein executing the machine-executable module causes the apparatus to perform the predictive modeling procedure, including: manipulating input data, comprising performing the pre-processing task on the input data; performing the model-fitting task, comprising: generating, from the pre-processed input data, training data and testing data, fitting a predictive model to the training data, and testing the fitted model on the testing data; and performing the post-processing task, wherein the pre-processed input data comprise at least one data set, wherein generating the training data comprises obtaining a first subset of the data set, and wherein generating the testing data comprises obtaining a second subset of the data set, wherein performing the predictive modeling procedure further includes performing cross-validation of the predictive model, wherein the training data are first training data, wherein the testing data are first testing data, wherein the fitted model is a first fitted model, and wherein performing the cross-validation of the predictive model comprises: (a) generating, from the data set, second training data and second testing data, wherein generating the second training data comprises obtaining a third subset of the data set, and wherein generating the second testing data comprises obtaining a fourth subset of the data set; (b) fitting the predictive model to the second training data to obtain a second fitted model; and (c) testing the second fitted model on the second testing data.