Abstract: An estimating device includes processing circuitry configured to estimate a median of intervals between adjacent data pieces in input time-series data as a uniform interval for the time-series data, and extract data pieces at the estimated uniform intervals from the input time-series data.

Abstract: A generating unit generates data with pseudo-correct answers by labeling unlabeled data with no correct answers on the basis of labeled data with correct answers using a plurality of prediction models for predicting a label from data, the prediction models being built according to different building procedures from one another. A calculating unit calculates the prediction accuracy of each of the prediction models using the data with correct answers and the data with the pseudo-correct answers. A determining unit determines a prediction model with a prediction accuracy calculated by the calculating unit satisfying a prescribed criterion.

Abstract: A detection device includes processing circuitry configured to compare data during learning and data during prediction for each feature amount of data and determine whether they are similar, and determine that accuracy of a model for outputting a predicted value of an objective variable of data has deteriorated when a ratio of a feature amount determined to be not similar to all feature amounts is equal to or greater than a predetermined threshold value.

Abstract: An estimating device includes processing circuitry configured to estimate a median of intervals between adjacent data pieces in input time-series data as a uniform interval for the time-series data, and extract data pieces at the estimated uniform intervals from the input time-series data.